Mean Aerosol Optical Thickness Research Articles

Aerosol impacts on the East Asian winter monsoon: Insights from TaiESM1 and CMIP6 simulations

AbstractThe East Asian winter monsoon (EAWM) is an important climate pattern in Southeast Asia. This study delved into the aerosol effects on the EAWM by analysing simulations conducted with the Taiwan Earth System Model version 1 (TaiESM1) model, part of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our assessment, validated against observational and reanalysis data, revealed that TaiESM1 effectively replicates the robust circulation of the EAWM and aerosol concentrations, placing its performance above average level among CMIP6 models. Notably, the simulated global mean aerosol optical thickness exhibited an approximately 20% increase from 1850 to 2014. The increased aerosols corresponded to a weakened Aleutian Low and an intensified Siberian High, leading to a weakened EAWM in the lower atmosphere over extratropical areas. In addition, the cooling across the Northern Hemisphere might affect enhanced northerly winds at approximately 10°N, which are situated in the southern part of the EAWM. An analysis of the near‐surface temperature budget indicated that the aerosol‐induced cooling in East China and India was primarily driven by changes in shortwave and longwave radiation fluxes, albeit slightly offset by sensible heat and latent heat fluxes. Furthermore, our study also reveals that while the mechanisms through which anthropogenic aerosols affect the northern portion of the EAWM vary across most CMIP6 models, their impacts on the tropical region remain consistent.

Regional transportation and influence of atmospheric aerosols triggered by Tonga volcanic eruption

A cataclysmic submarine volcano at Hunga Tonga-HungaHa'apai (HTHH) near Tonga, erupted violently on 15 January 2022, which injected a plume of ash cloud soaring into the upper atmosphere. In this study, we examined the regional transportation and potential influence of atmospheric aerosols triggered by HTHH volcano, based on active and passive satellite products, ground-based observations, multi-source reanalysis datasets and atmospheric radiative transfer model. The results indicated that about 0.7 Tg (1 Tg = 109 kg) sulfur dioxide (SO2) gas were emitted into stratosphere from the HTHH volcano, and were lifted to an altitude of 30 km. The regional averaged SO2 columnar content over the western Tonga increased by 10–36 Dobson Units (DU), and the mean aerosol optical thickness (AOT) retrieved from satellite products increased to 0.25–0.34. The stratospheric AOT values caused by HTHH emissions increased to 0.03, 0.20, and 0.23 on 16, 17, and 19 January, respectively, accounting for 1.5%, 21.9%, and 31.1% of total AOT. Ground-based observations also showed an AOT increase of 0.25–0.43, with the maximum daily average of 0.46–0.71 appeared on 17 January. The volcanic aerosols were remarkably dominated by fine-mode particles and posed strong light-scattering and hygroscopic abilities. Consequently, the mean downward surface net shortwave radiative flux was reduced by 2.45–11.9 Wm-2 on different regional scales, and the surface temperature decreased by 0.16–0.42 K. The maximum aerosol extinction coefficient was 0.51 km−1 appeared at 27 km, which resulted in an instantaneous shortwave heating rate of 1.80 Khour−1. These volcanic materials stayed stable in the stratosphere and completed one circle around the earth within 15 days. This would exert a profound influence on the energy budget, water vapor and ozone exchange in the stratosphere, which deserves to be further studied.

The Global Atmosphere-aerosol Model ICON-A-HAM2.3-Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness.

The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3‐HAM2.3 global atmosphere‐aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON‐A (icon‐aes‐1.3.00) global atmosphere model to yield the new ICON‐A‐HAM2.3 atmosphere‐aerosol model. The ICON‐A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub‐grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6‐HAM2.3 two‐moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON‐A‐HAM2.3 and ECHAM6.3‐HAM2.3, but the bias is larger in ICON‐A‐HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub‐tropical oceans. ICON‐A‐HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON‐A‐HAM2.3 compared to standard ICON‐A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON‐A‐HAM2.3 and in ECHAM6.3‐HAM2.3. In the extra‐tropics, a smaller multivariable bias is found for ICON‐A‐HAM2.3 than for ECHAM6.3‐HAM2.3.

The Impact of COVID-19 Lockdowns on Satellite-Observed Aerosol Optical Thickness over the Surrounding Coastal Oceanic Areas of Megacities in the Coastal Zone

Nearly 40 years of aerosol optical thickness (AOT) climate data record (CDR) derived from NOAA operational satellite Advanced Very High Resolution Radiometer (AVHRR) observation over the global oceans is used to study the AOT changes due to the COVID-19 lockdown over the surrounding coastal oceanic areas of 18 megacities in the coast zone (MCCZ). The AOT difference between the annual mean AOT values of 2020 with COVID-19 lockdown and 2019 without the lockdown along with the 2020 AOT annual anomaly are used to effectively identify the AOT changes that are a result of the lockdown. We found that for most of the 18 MCCZ, the COVID-19 lockdowns implemented to contain the spread of the coronavirus resulted in a decrease between 1% and 30% in AOT due to reduced anthropogenic emissions associated with the lockdowns. However, the AOT long-term trend and other aerosol interannual variations due to favorable or unfavorable meteorological conditions may mask AOT changes due to the lockdown effect in some MCCZ. Different seasonal variations of aerosol amount in 2020 relative to 2019 due to other natural aerosol emission sources not influenced by the lockdown, such as dust storms and natural biomass burning and smoke, may also conceal a limited reduction in the annual mean AOT due to the lockdown in MCCZ with relatively loose lockdown. This study indicates that the use of long-term satellite observation is helpful for studying and monitoring the aerosol changes due to the emission reduction associated with the COVID-19 lockdown in the surrounding coastal oceanic areas of MCCZ, which will benefit the future development of the mitigation strategy for air pollution and emissions in megacities.

The contribution of different aerosol types to direct radiative forcing over distinct environments of Pakistan inferred from the AERONET data

To quantitatively estimate and analyze the contribution of different aerosol types to radiative forcing, we thoroughly investigated their optical and radiative properties using the Aerosol Robotic Network (AERONET) data (2007–2018) over an urban-industrial (Lahore) and coastal (Karachi) cities located in Pakistan. The contribution of inferred aerosol types following the threshold applied for FMF500 versus SSA440 and EANG440−870 versus AANG440−870 were found the highest for pure dust (PUD, 31.90%) followed by polluted continental (POC, 24.77%) types of aerosols, with moderate contribution was recorded for polluted dust (POD, 20.92%), organic carbon dominating (OCD, 11.85%), black carbon dominating (BCD, 8.77%) and the lowest for the non-absorbing (NOA, 1.79%) aerosol type. Seasonally, the mean (±SD) aerosol optical thickness at 440 nm (AOT440) was found maximum (0.73 ± 0.36) for PUD type in summer and minimum for BCD (0.25 ± 0.04) during spring at Karachi. However, the mean (±SD) AOT440 varied from 0.85 ± 0.25 during summer to 0.57 ± 0.30 in winter at Lahore, with the highest contributions for POC (29.91%) and BCD (22.58%) and the lowest for NOA (5.85%) type of aerosols. Further, the intensive optical properties showed significant temporal and spectral changes and the complexity of inferred aerosol types over the study sites. The results are well substantiated with the air mass analysis obtained from the concentration weighted trajectory (CWT) model for different aerosol types. The Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model revealed the strong presence of BCD aerosol type led to a surface (BOA) and top of atmosphere (TOA) forcing of −70.12, −99.78 Wm−2 and −9.60, −19.74 Wm−2, with an annual heating rate of 2.10 and 2.54 Kday−1, respectively, at Karachi and Lahore sites.

The spatio-temporal characteristics of aerosol optical thickness as well as the relationship with PM2.5 in Xiamen city, China

Long-term aerosol optical thickness (AOT) composited data (2002-2017) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft was used to evaluate the temporal and spatial variability of aerosol in Xiamen city by using wavelet analysis, and the relationship between the surface mass concentrations of particulate matter with aerodynamic diameters less than 2.5 μm (PM2.5) and the AOT was analyzed by using linear regression. The results showed that AOT increased gradually from 2002 to 2011, and then decreased. AOT displayed a significant 9-month periodicity in AOT was inferred wavelet analysis. AOT also showed significant annual variability in response to changes in weather and aerosol pollution. We observed highest AOT values in April, with a monthly mean of 1.00 ± 0.18. Lowest values were observed in December, with a mean AOT of 0.52 ± 0.11. Multi-year monthly AOT fluctuations were lowest in January with a low variation coefficient (0.14), and the largest fluctuations appeared in July with a high variation coefficient (0.29). Higher AOT values (~ 1.1) were predominantly located in the southern urban areas of Xiamen and lower AOT values (~ 0.3) were mainly located in northern rural regions. The aerosol pollution was serious in April with the smallest spatial variation coefficient of 0.25, and the highest spatial variation coefficient appeared in July. Highest intraannual variability predominantly occurred in the high-value areas in the center of Xiamen. AOT values remained high in Xiamen Island throughout the year with a multi-year mean of 0.87. There was a moderate correlation between ground-based PM2.5 and MODIS AOT. Therefore, we confirm the suitability of MODIS AOT to accurately estimate PM2.5 concentration and evaluate the temporal and spatial characteristics of air quality in Xiamen.

Spatial and temporal gradients in the rate of dust deposition and aerosol optical thickness in southwestern Iran

The southwestern Iran is one of the regions that are most prone to dust events. The objective of this study is the analysis of the spatial and temporal distributions of dust deposition rate as a key factor for finding the relative impact of the dust. First, the monthly mean aerosol optical thickness (AOT) from Moderate Resolution Imaging Spectroradiometer (MODIS) was analyzed and compared with the dust amount variations from ground deposition rate (GDR), and the results were further used to investigate the spatial and temporal distributions of dust events in southwestern Iran for the period between 2014 and 2015. Moving air mass trajectories, using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, were proven to be a discriminator of their local and regional origin. The results from GDR analysis produced a correlation coefficient between dust event history and deposition rates at dust magnitudes of >0.93 that is meaningful at the 95% confidence level. Furthermore, the deposition rates varied from 3 g/m2 per month in summer to 10 g/m2 per month in spring and gave insight into the transport direction of the dust. Within the same time series, AOT correspondences with MODIS on Terra in four aerosol thickness layers (clean, thin, thick, and strong thick) were shown in relation to each other. The deepest mixed layers were observed in spring and summer with a thickness of approximately 3500 m above ground level in the study area. Investigations of ground-based observations were correlated with the same variations for each aerosol thickness layer from MODIS images and they can be applied to discriminate layers of aeolian dust from layers of other aerosols. Together, dust distribution plots from AOT participated to enhance mass calculations and estimation deposition rates from the thick and strong thick aerosol thickness layers using the results from GDR. Despite all the advances of AOT, under certain circumstances, ground-based observations are better able to represent aerosol conditions over the study area, which were tested in southwestern Iran, even though the low number of observations is a commonly acknowledged drawback of GDR.

AEROSOL PLUMES CHARACTERIZATION BY HYPERSPECTRAL IMAGES COUPLED WITH SENTINEL-2 PRODUCTS

Abstract. In this paper, we focus on the retrieval of microphysical and optical properties of industrial aerosol plumes through a process using airborne hyperspectral and Sentinel-2 multi-spectral images. The process allows first to perform atmospheric correction and second to determine background aerosols thanks to a comparison between hyperspectral and Sentinel-2 reflectances. Hyperspectral methodologies use the radiance differential between the measurement in the plume and the corresponding measurements out of the plume to estimate plume properties. To retrieve the surface reflectance under the plume, a principal component analysis coupling hyperspectral and multispectral data class by class is achieved. The developed method aims to compare the difference between measured and estimated reflectance with a radiative transfer model accounting for plume properties (particle radius and aerosol optical thickness of the plume). We have applied the method to a steel plant in the south of France. The retrieved plume show an aerosol mean radius between 0.05 and 0.2 µm with a mean aerosol optical thickness about 0.05 along the plume.

Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product

Abstract. We estimated the distribution of aerosol optical thickness (AOT) with a spatial resolution of 1 km over the Moscow megacity using the MAIAC aerosol product based on MODIS satellite data (Lyapustin et al., 2018) for the warm period of the year (May–September, 2001–2017). AERONET (Aerosol Robotic Network)-based validation of satellite estimates near the city centre at Moscow_MSU_MO and over the Moscow suburbs at Zvenigorod revealed that MAIAC AOT at 0.47 µm is in agreement with AERONET AOT though underestimated by 0.05–0.1 for AOT<1 and overestimated for smoke conditions with AOT>1. The MAIAC AOT biases were almost the same for the Moscow_MSU_MO and Zvenigorod AERONET sites, which indicated that the MAIAC algorithm effectively removed the effect of the bright urban surface in the city centre. For the ground-based measurements, the difference between annual median AOT at Moscow_MO_MSU and Zvenigorod (ΔAOT) varied within −0.002 to +0.03, with statistically significant positive bias for most years, and an average ΔAOT was about 0.02. According to the MAIAC dataset, the ΔAOT varied within ±0.01 and was not statistically significant. The ΔAOT started decreasing recently due to intensive urban development of the territory around Zvenigorod and the decrease in pollutant emissions in Moscow, which is mainly caused by the environmental regulations. According to the MAIAC dataset, the most pronounced spatial AOT differences over the territory of Moscow were observed at the 5 % quantile level, where they reached 0.05–0.06 over several locations and could be attributed to the stationary sources of aerosol pollution, for example, large areas of construction sites, aerosol pollution from roads and highways, or agriculture activities. The differences between the maximum and the mean AOT for different quantiles, except the 95 % quantile, within the Moscow region, were about 0.02–0.04, which could be attributed to the local aerosol sources. The application of the MAIAC algorithm over the whole Moscow region has revealed a decreasing AOT trend over the centre of Moscow and an increasing trend over the “New” Moscow territory which experienced an intensive build-up and agricultural development.

Intra-annual variations of regional total column ozone, aerosol optical depth, and water vapor from ground-based, satellite-based and model-based observations

Abstract The Microtops II ozonometer has been deployed to continuously measure the total column ozone (TCO), precipitable water content (PWC) and aerosol optical thickness (AOT) at Atigre village (16.74° N, 74.37° E, 604 m above sea level, masl) located on the southeastern slope of Indian western Ghats. The Microtops II ozonometer measurements during the period from September 2017 to June 2018 were analyzed along with the retrieved products of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellites and also the ERA-interim reanalysis model. We found that the TCO (or PWC) data from the OMI (or MODIS) and the ERA reanalysis model data products are in good agreement. The measurements showed strong seasonal variability such that TCO was lowest in the winter season but increased in the summer season, and both PWC and AOT were lowest in the post-monsoon season and increased in the summer season. In continuous ERA-interim reanalysis TCO observations, we found the three types of periodicities in the daily mean TCO as well as PWC (i) The weekly (7 days), (ii) quasi-biweekly (14 to 16 days), (iii) Madden Julian Oscillations (MJO) (30–60 days) oscillations. These oscillations depend on the periodic weather changes in the troposphere. We also observe that the average day to day variability in daily mean TCO observations in the observational period is about 1.4%, 1.1%, 2.62% in the Microtops II ozonometer, ERA-interim reanalysis, and OMI data respectively. We found the positive correlation between daily mean AOT and PWC in all seasons (except monsoon), which is maximum in the winter season, showing the hygroscopic nature of aerosols. The sources of water vapor and aerosol at our location are also studied using back-trajectory analysis.

PERFORMANCE OF AHI HOURLY AEROSOL OPTICAL PROPERTY DURING FREQUENT HAZE-FOG EVENTS: A CASE STUDY OF BEIJING

Abstract. The Advanced Himawari Imager (AHI) onboard Himawari-8, a next-generation geostationary meteorological satellite, provided firstly the full-disk aerosol observations every 10 min at sub-kilometer spatial resolution(5 km). This is responsible for retrieving the ground-level particulate matter of fewer than 2.5 micrometers and improving assimilation model. However, the representativeness of AHI L3 hourly Aerosol Optical Thickness (AOT) products remains unclear under different air quality conditions, Especially, over frequently polluted urban areas that feature complex surface characteristics and aerosol models. In this study, One-to-one comprehensive comparisons were conducted to evaluate the performance of three types of AHI L3 AOT products (version 3.0) based on the Aerosol Robotic NETwork (AERONET) aerosol measurements over Beijing. The overall comparisons of AHI and ground AOTs show the AHI merged AOT perform best, which the R is 0.87, RMSE is 0.25 and 52.5% of retrievals fall within the envelope of Expect Error (EE, ±(0.05 + 0.2 * AOTground)). For the different primary pollutants, the results suggested the three types AHI hourly AOT products are more suitable for the fine particulate matters (PM2.5) retrievals, especially the merged AOT with 0.87 of R, 0.29 of RMSE and 58.8% of within EE. Furthermore, when the slight and moderate pollution happened over Beijing, the AHI hourly AOT products perform well. And when the heavy pollution happened, the performance of the AHI merge AOT and L2 mean AOT is better. a case during low to high pollution suggested that AHI merged AOT can capture the similar spatial pattern to the MODIS (Deep Blue) DB or (Dark Target) DTDB merged AOT and has good consistency with ground-based air quality monitoring. These results demonstrate the AHI hourly merged AOT is a promising aerosol retrieval for air quality.

The climatology of aerosol optical thickness and radiative effects in Southeast Asia from 18-years of ground-based observations

The present study utilizes 18 years of long-term (2001–2018) data collected from six active AERONET sites over the Indo-Gangetic Plain (IGP) and the North China Plain (NCP) areas in Southeast Asia. The annual mean (±SD) aerosol optical thickness at 440 nm (AOT440) was found high at XiangHe (0.92 ± 0.69) and Taihu (0.90 ± 0.51) followed by Beijing (0.81 ± 0.69), Lahore (0.81 ± 0.43), and Kanpur (0.73 ± 0.35) and low at Karachi (0.52 ± 0.23). Seasonally, high AOT440 with corresponding high Ångström exponent (ANG440-870) noticed during JJA for all sites, except Kanpur, suggesting the dominance of fine-mode particles, generally associated with large anthropogenic emissions. Climatologically, an increasing (decreasing) trend was observed over IGP (NCP) sites, with the highest (lowest) percentage of departures in AOT440 found over Beijing (Karachi). We further identified major aerosol types which showed the dominance of biomass burning, urban-industrial followed by the mixed type of aerosols. In addition, single scattering albedo (SSA), asymmetry parameter (ASP), volume size distribution (VSD), and complex aerosol refractive index (RI) showed significant temporal and spectral changes, illustrating the complexity of aerosol types. At last, the annual mean direct aerosol radiative forcing at the top, bottom, and within the atmosphere for all sites were found in the range from −17.36 ± 3.75 to −45.17 ± 4.87 W m−2, -64.6 ± 4.86 to −93.7 ± 10.27 W m−2, and 40.5 ± 6.43 to 68.25 ± 7.26 W m−2, respectively, with an averaged atmospheric heating rate of 0.9–2.3 K day−1. A large amount of anthropogenic aerosols showed a significant effect of heating (cooling) on the atmosphere (surface) results obviously, due to an increased rate of atmospheric heating. Therefore, the thermodynamic effects of anthropogenic aerosols on the atmospheric circulation and its structure should be taken into consideration for future study over the experimental sites.

Estimation and Validation of Collection 6 Moderate Resolution Imaging Spectroradiometer Aerosol Products for East Asia

The operational aeroscthm, a substantially improved version of the collection 5 (C5) algorithm, uses an enhanced aerosol optical thickness (AOT) retrieval process consisting of new surface reflection and aerosol models. This study reports on the estimation and validation of the two latest versions, the C5 and C6 MODIS aerosol products over the East Asian region covering 20°N to 56°N and 80°E to 150°E. This study also presents a comparative validation of the two versions(C5 and C6) of algorithms with different methods (Dark Target(DT) and Deep Blue (DB) retrieval methods) from the Terra and Aqua platforms to make use of the Aerosol Robotic Network(AERONET) sites for the years 2000–2016. Over the study region, the spatially averaged annual mean AOT retrieved from C6 AOT is about 0.035(5%) less than the C5 counterparts. The linear correlations between MODIS and AERONET AOT are R = 0.89 (slope = 0.86) for C5 and R = 0.95 (slope = 1.00) for C6. Moreover, the magnitude of the mean error in C6 AOT-the difference between MODIS AOT and AERONET AOT-is 40% less than that in C5 AOT.

Long term characteristics of aerosols over Pune, central India - Effect on radiative forcing

Sun photometer (MICROTOPS II) and Sun-sky radiometer (POM-02, Prede) data for 2003-2013 period are used to study the optical and temporal characteristics of aerosols and their effect on radiative forcing over Pune, central India. The daily mean aerosol optical thickness at 500 nm (AOT500) and Angstrom exponent for the study period were 0.77 ± 0.22 0.92 ± 0.24 respectively. Short wave aerosol radiative forcing (ARF) computed for the year 2013 using Santa Barbara Discrete-ordinate Atmospheric Radiative Transfer (SBDART) model, showed ARF at surface (SUF) and top of the atmosphere (TOA) was negative indicating dominance of scattering type aerosols. AOT, single scattering albedo (SSA) and asymmetry parameter (ASP) derived from Sun sky radiometer showed more AOT and ASP and less SSA during April / May to August indicating prevalence of absorbing soil dust in this period. Atmospheric heating varied from +14.3 to 20.5 W/m2 and was more in monsoon (+ 35.4 W/m2). ARF at SUF was found to be a strong function of AOT500 (R2= 0.90). The radiative forcing efficiency inferred to scattering nature of aerosols at SUF (-66.2 W/m2/ AOT), TOA (- 0.2 W/m2 / AOT) and atmosphere (ATM) (+ 66.0 W/m2 /AOT). The atmospheric heating rates varied from 0.94 K/day in post monsoon to 2.78 K/day in monsoon. Monthly, seasonal and diurnal variability of AOT500 and with role of meteorological factors are also discussed.

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean*

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a year-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5° spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

Analysis of the 2014 “APEC Blue” in Beijing Using More than One Decade of Satellite Observations: Lessons Learned from Radical Emission Control Measures

During the 2014 Asia-Pacific Economic Cooperation (APEC) Economic Leaders’ Meetings in Beijing, the Chinese government made significant efforts to clear Beijing’s sky. The emission control measures were very effective and the improved air quality during the APEC Meetings was called the “APEC Blue”. To monitor and estimate how these emission control measures affected air quality in Beijing and its five neighboring large cities (Tianjin, Shijiazhuang, Tangshan, Jinan, and Qingdao), we compared and analyzed the satellite-retrieved Aerosol Optical Thickness (AOT) products of the pre-APEC (18–31 October), APEC (1–11 November), and post-APEC periods (11–31 November) in 2002–2014 and daily PM2.5 measurements of the three periods in 2014 on the ground. Compared with the pre- and post-APEC periods, both ground and satellite observations indicated significantly reduced aerosol loading during the 2014 APEC period in Beijing and its surroundings, but with apparent spatial heterogeneity. For example, the peak value of PM2.5 in Beijing were around 100 µg∙m−3 during the APEC period, however, during the pre- and post-APEC periods, the peak values were up to 290 µg∙m−3. The following temporal correlation analysis of mean AOT values between Beijing and other five cities for the past thirteen years (2002–2014) indicated that the potential emission source regions strongly impacting air quality of Beijing were confined within central and southern Hebei as well as northern and southwestern Shandong, in correspondence with the spatial pattern of Digital Earth Model (DEM) of the study region. In addition to stringent emission control measures, back trajectory analysis indicated that the relatively favorable regional transport pattern might also have contributed to the “APEC Blue” in Beijing. These results suggest that the “APEC Blue” is a temporarily regional phenomenon; a long-term improvement of air quality in Beijing is still challenging and joint efforts of the whole region are needed.

Validation of Long-Term Global Aerosol Climatology Project Optical Thickness Retrievals Using AERONET and MODIS Data

A comprehensive set of monthly mean aerosol optical thickness (AOT) data from coastal and island AErosol RObotic NETwork (AERONET) stations is used to evaluate Global Aerosol Climatology Project (GACP) retrievals for the period 1995–2009 during which contemporaneous GACP and AERONET data were available. To put the GACP performance in broader perspective, we also compare AERONET and MODerate resolution Imaging Spectroradiometer (MODIS) Aqua level-2 data for 2003–2009 using the same methodology. We find that a large mismatch in geographic coverage exists between the satellite and ground-based datasets, with very limited AERONET coverage of open-ocean areas. This is especially true of GACP because of the smaller number of AERONET stations at the early stages of the network development. Monthly mean AOTs from the two over-the-ocean satellite datasets are well-correlated with the ground-based values, the correlation coefficients being 0.81–0.85 for GACP and 0.74–0.79 for MODIS. Regression analyses demonstrate that the GACP mean AOTs are approximately 17%–27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%–25% higher. The regression coefficients are highly dependent on the weighting assumptions (e.g., on the measure of aerosol variability) as well as on the set of AERONET stations used for comparison. Comparison of over-the-land and over-the-ocean MODIS monthly mean AOTs in the vicinity of coastal AERONET stations reveals a significant bias. This may indicate that aerosol amounts in coastal locations can differ significantly from those in adjacent open-ocean areas. Furthermore, the color of coastal waters and peculiarities of coastline meteorological conditions may introduce biases in the GACP AOT retrievals. We conclude that the GACP and MODIS over-the-ocean retrieval algorithms show similar ranges of discrepancy when compared to available coastal and island AERONET stations. The factors mentioned above may limit the performance of the validation procedure and cause us to caution against a direct extrapolation of the presented validation results to the entirety of the GACP dataset.

Retrieval of High-Resolution Atmospheric Particulate Matter Concentrations from Satellite-Based Aerosol Optical Thickness over the Pearl River Delta Area, China

Satellite remote sensing offers an effective approach to estimate indicators of air quality on a large scale. It is critically significant for air quality monitoring in areas experiencing rapid urbanization and consequently severe air pollution, like the Pearl River Delta (PRD) in China. This paper starts with examining ground observations of particulate matter (PM) and the relationship between PM10 (particles smaller than 10 μm) and aerosol optical thickness (AOT) by analyzing observations on the sampling sites in the PRD. A linear regression (R2 = 0.51) is carried out using MODIS-derived 500 m-resolution AOT and PM10 concentration from monitoring stations. Data of atmospheric boundary layer (ABL) height and relative humidity are used to make vertical and humidity corrections on AOT. Results after correction show higher correlations (R2 = 0.55) between extinction coefficient and PM10. However, coarse spatial resolution of meteorological data affects the smoothness of retrieved maps, which suggests high-resolution and accurate meteorological data are critical to increase retrieval accuracy of PM. Finally, the model provides the spatial distribution maps of instantaneous and yearly average PM10 over the PRD. It is proved that observed PM10 is more relevant to yearly mean AOT than instantaneous values.

Extension and statistical analysis of the GACP aerosol optical thickness record

The primary product of the Global Aerosol Climatology Project (GACP) is a continuous record of the aerosol optical thickness (AOT) over the oceans. It is based on channel-1 and -2 radiance data from the Advanced Very High Resolution Radiometer (AVHRR) instruments flown on successive National Oceanic and Atmospheric Administration (NOAA) platforms. We extend the previous GACP dataset by four years through the end of 2009 using NOAA-17 and -18 AVHRR radiances recalibrated against MODerate resolution Imaging Spectroradiometer (MODIS) radiance data, thereby making the GACP record almost three decades long. The temporal overlap of over three years of the new NOAA-17 and the previous NOAA-16 record reveals an excellent agreement of the corresponding global monthly mean AOT values, thereby confirming the robustness of the vicarious radiance calibration used in the original GACP product. The temporal overlap of the NOAA-17 and -18 instruments is used to introduce a small additive adjustment to the channel-2 calibration of the latter resulting in a consistent record with increased data density. The Principal Component Analysis (PCA) of the newly extended GACP record shows that most of the volcanic AOT variability can be isolated into one mode responsible for ~12% of the total variance. This conclusion is confirmed by a combined PCA analysis of the GACP, MODIS, and Multi-angle Imaging SpectroRadiometer (MISR) AOTs during the volcano-free period from February 2000 to December 2009. We show that the modes responsible for the tropospheric AOT variability in the three datasets agree well in terms of correlation and spatial patterns. A previously identified negative AOT trend which started in the late 1980s and continued into the early 2000s is confirmed. Its magnitude and duration indicate that it was caused by changes in tropospheric aerosols. The latest multi-satellite segment of the GACP record shows that this trend tapered off, with no noticeable AOT change after 2002. This result is consistent with the MODIS and MISR AOT records as well as with the recent gradual reversal from brightening to dimming revealed by surface flux measurements in many aerosol producing regions. Thus the robustness of the GACP record is confirmed, increasing our confidence in the validity of the negative trend. Although the nominal negative GACP AOT trend could partially be an artifact of increasing aerosol absorption, we argue that the time dependence of the GACP record, including the latest flat period, is more consistent with the actual decrease in the tropospheric AOT.

Spatio-temporal variability of Suomi-NPP VIIRS-derived aerosol optical thickness over China in 2013

The Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical thickness (AOT) at 550 nm Intermediate Product (IP) data was evaluated by comparing it with measurements from Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals. The spatial and temporal variations in the regional AOT over China during 2013 (from 24 January to 31 December) were then firstly investigated using VIIRS aerosol IP data. Evaluation of VIIRS IP AOT with MODIS retrievals and AERONET measurements indicated that the performance of the VIIRS aerosol IP product is comparable to that of their counterparts from the heritage MODIS sensor. However, the VIIRS IP can produce more retrievals than MODIS due to its higher spatial resolution, therefore more suitable for regional AOT study. It was found that the VIIRS IP mean AOT over China differs from that of MODIS by −0.032 for the collocated retrievals, with a correlation of 0.928. Compared with AERONET measurements, VIIRS IP AOT shows a negative bias of −0.058 with the standard deviation of the difference of 0.192 over China. Among the 10 typical sites under study, the maximum annual average AOT550 values (with±standard deviation) were found in Chengdu (1.07±0.32), whereas the lowest annual mean AOT550 values were found in FB1 (0.242±0.25). The economically developed regions had high AOT values during all seasons. Based on the distribution of AOT, China can be divided into an economically developed eastern region with high AOT values and less-developed western regions, consistent with the boundary between China’s second and third terrain regions.