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At least 217 records · Page 12

Parameterizing Spectral Surface Reflectance Relationships for the Dark Target Aerosol Algorithm Applied to A Geostationary Imager

Originally developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) in polar, sun-synchronous low-earth orbit (LEO), the Dark Target (DT) aerosol retrieval algorithm relies on the assumption of a Surface Reflectance Parameterization (SRP) over land surfaces. Specifically for vegetated and dark-soiled surfaces, values of surface reflectance in blue and red visible-wavelength bands are assumed to be nearly linearly related to each other and to the value in a shortwave infrared (SWIR) wavelength band. This SRP also includes dependencies on scattering angle and a normalized difference vegetation index computed from two SWIR bands (NDVISWIR). As the DT retrieval algorithm is being ported to new sensors to continue and expand the aerosol data record, we assess whether the MODIS-assumed SRP can be used for these sensors. Here, we specifically assess SRP for the Advanced Baseline Imager (ABI) aboard, the Geostationary Operational Environmental Satellite (GOES)-16/East (ABIE). First, we find that using MODIS-based SRP leads to higher biases and artificial diurnal signatures in aerosol optical depth (AOD)retrievals from ABIE. The primary reason appears to be that geostationary orbit (GEO) encounters an entirely different set of observation geometry than does LEO, primarily with regards to solar angles coupled with fixed view angles. Therefore, we have developed a new SRP for GEO that draws the angular shape of the surface bidirectional reflectance. We also introduce modifications to the parametrization of both red-SWIR and blue-red spectral relationships to include additional information.The revised Red-SWIR SRP includes solar zenith angle, NDVISWIR, and land-type percentage from an ancillary database. The blue-red SRP adds dependencies on the scattering angle and NDVISWIR. The new SRPs improve the AOD retrieval of ABIE in terms of overall less bias and mitigation of the overestimation around local noon. The average bias of DT AOD compared to AERONET AOD shows a reduction from 0.08 to 0.03, while the bias of local solar noon decreases from 0.12 to 0.03.The agreement between DT and AERONET AOD is established through regression slope of 1.06 and y-intercept of 0.01with correlation coefficient is0.74. By using the new SRP, the percentage of data falling within the expected error range (±0.05 + 15%) is notably risen from 54% to 78%.

Mijin Kim↗

A New Retrieval of Aerosol Optical Depth from Reflectance Ratios on Partly Cloudy Days: Development and Evaluation

The aerosol optical depth (AOD) is an important parameter for describing the Earth’s radiation budget and hydrologic cycle and it is critical in the context of the cloud-aerosol-precipitation problem. The extracting AOD from satellite-measured cloudy-sky reflectances represents a great challenge in remote sensing studies, where cloud-induced artifacts can be responsible for large uncertainties (up to 140%) in the satellite-derived AOD. We have developed a new method, named the reflectance ratio (RR) method, which presents an effective way to reduce substantially the impact of the cloud contamination on the retrieved AOD. The RR method relies on the well-established fact that clouds reflect about the same amount of sunlight regardless of the wavelength, and thus the reflectance ratio is less sensitive to the radiative effects of clouds than reflectance. For partly cloudy conditions, we examined performance of the RR method using a case study and demonstrated that the RR method has an opportunity to obtain accurate (~5%) and reasonable (~15-30%) estimations of domain-averaged AOD between clouds at 660-nm wavelength and 470-, 870-nm wavelengths, respectively .

Kassianov, Evgueni I.↗

Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading

Quantifying aerosol compositions (e.g., type, loading) from remotely sensed measurements by spaceborne, suborbital and ground-based platforms is a challenging task. In this study, the first and second-order spectral derivatives of aerosol optical depth (AOD) with respect to wavelength are explored to determine the partitions of the major components of aerosols based on the spectral dependence of their particle optical size and complex refractive index. With theoretical simulations from the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) model, AOD spectral derivatives are characterized for collective models of aerosol types, such as mineral dust (DS) particles, biomass-burning (BB) aerosols and anthropogenic pollutants (AP), as well as stretching out to the mixtures among them. Based on the intrinsic values from normalized spectral derivatives, referenced as the Normalized Derivative Aerosol Index (NDAI), a unique pattern is clearly exhibited for bounding the major aerosol components; in turn, fractions of the total AOD (fAOD) for major aerosol components can be extracted. The subtlety of this NDAI method is examined by using measurements of typical aerosol cases identified carefully by the ground-based Aerosol Robotic Network (AERONET) sun–sky spectroradiometer. The results may be highly practicable for quantifying fAOD among mixed-type aerosols by means of the normalized AOD spectral derivatives.

aerosol partition↗

Retrieval of Aerosol Optical Properties From GOCI-II Observations: Continuation of Long-Term Geostationary Aerosol Monitoring Over East Asia

Since the Geostationary Ocean Color Imager (GOCI) was successfully launched in 2010, the GOCI Yonsei aerosol retrieval (YAER) algorithm has been continuously updated to retrieve hourly aerosol optical properties. GOCI-II has 4 more channels including UV, finer spatial resolution (250 m), and daily full disk coverage as compared to GOCI, and was launched in February 2020, onboard the GEO-KOMPSAT-2B (GK-2B) satellite. In this study, we extended the YAER algorithm to GOCI-II data based on its improved performance in many aspects and present the first results of aerosol optical properties retrieved from GOCI-II data. Utilizing the overlapping period between the GOCI-II and GOCI in geostationary Earth orbit, we present GOCI-II aerosol retrievals for high aerosol-loading cases over East Asia and show that these have a consistent spatial distribution with those from GOCI. Furthermore, GOCI-II provides AOD at an even higher spatial resolution, revealing finer changes in aerosol concentrations. Validation results for one year data show that the GOCI-II AOD has a correlation coefficient of 0.83 and a ratio within the expected error (EE) of 59.4 % when compared with the aerosol robotic network (AERONET) data. We compared statistical metrics for the GOCI and GOCI-II AODs to assess the consistency between the two datasets. In addition, it was found that there is a strong correlation between the two datasets from the comparison of gridded GOCI and GOCI-II AOD products. It is expected that data from GOCI-II will continue long-term aerosol records with high accuracy that can be used to address air-quality issues over East Asia.

AOD↗

Rain-aerosol relationships influenced by wind speed: RAIN-AEROSOL RELATIONSHIPS

The aerosol optical depth (AOD) has been shown to correlate with precipitation rate (R) in recent studies. The relationships between R and AOD are examined in this study using 150-year simulations in preindustrial conditions with the CESM model. Through partial correlation analysis, with the impact from 10-m wind speed removed, relationships between modeled AOD and R exert a significant change from positive to negative over the mid-latitude oceans, indicating that the wind speed has the largest contribution to the relationships over the mid-latitude oceans. Sensitivity simulation shows that variations in wind speed lead to increasing R by +0.99 mm day-1 averaged globally, offsetting 64% of the wet scavenging induced decrease in precipitation between polluted and clean conditions. These demonstrate that wind speed is one of the major drivers of R-AOD relationships. Relative humidity can also result in the positive relationships; however, its role is smaller than that of wind speed.

54 ENVIRONMENTAL SCIENCES↗

WRF-Chem Simulations of Aerosols and Anthropogenic Aerosol Radiative Forcing in East Asia

This study aims to provide a first comprehensive evaluation of WRF-Chem for modeling aerosols and anthropogenic aerosol radiative forcing (RF) over East Asia. Several numerical experiments were conducted from November 2007 to December 2008. Comparison between model results and observations shows that the model can generally reproduce the observed spatial distributions of aerosol concentration, aerosol optical depth (AOD) and single scattering albedo (SSA) from measurements at different sites, including the relatively higher aerosol concentration and AOD over East China and the relatively lower AOD over Southeast Asia, Korean, and Japan. The model also depicts the seasonal variation and transport of pollutions over East Asia. Particulate matter of 10 um or less in the aerodynamic diameter (PM10), black carbon (BC), sulfate (SO42-), nitrate (NO3-) and ammonium (NH4+) concentrations are higher in spring than other seasons in Japan due to the pollutant transport from polluted area of East Asia. AOD is high over Southwest and Central China in winter, spring and autumn and over North China in summer while is low over South China in summer due to monsoon precipitation. SSA is lowest in winter and highest in summer. The model also captures the dust events at the Zhangye site in the semi-arid region of China. Anthropogenic aerosol RF is estimated to range from -5 to -20 W m-2 over land and -20 to -40 W m-2 over ocean at the top of atmosphere (TOA), 5 to 30 W m-2 in the atmosphere (ATM) and -15 to -40 W m-2 at the bottom (BOT). The warming effect of anthropogenic aerosol in ATM results from BC aerosol while the negative aerosol RF at TOA is caused by scattering aerosols such as SO4 2-, NO3 - and NH4+. Positive BC RF at TOA compensates 40~50% of the TOA cooling associated with anthropogenic aerosol.

aerosol↗

Wave like signatures in aerosol optical depth and associated radiative impacts over the central Himalayan region

Doppler Lidar and Multi-Filter Rotating Shadowband Radiometer (MFRSR) observations are utilized to show wave like signatures in aerosol optical depth (AOD) during daytime boundary layer evolution over the Himalayan region. Fourier analysis depicted 60–80 min periods dominant during afternoon hours, implying that observed modulations could be plausible reason for the AOD forenoon–afternoon asymmetry which was previously reported. Inclusion of wave amplitude in diurnal variation of aerosol radiative forcing estimates showed ~40% additional warming in the atmosphere relative to mean AOD. The present observations emphasize the importance of wave induced variations in AOD and radiation budget over the site.

Aerosol optical depth↗

Climatology of aerosol optical depth in north-central Oklahoma: 1992–2008

Aerosol optical depth (AOD) has been measured at the Atmospheric Radiation Measurement Program central facility near Lamont, Oklahoma, since the fall of 1992. Most of the data presented are from the multifilter rotating shadowband radiometer, a narrow-band, interference-filter Sun radiometer with five aerosol bands in the visible and near infrared; however, AOD measurements have been made simultaneously and routinely at the site by as many as three different types of instruments, including two pointing Sun radiometers. Scatterplots indicate high correlations and small biases consistent with earlier comparisons. The early part of this 16 year record had a disturbed stratosphere with residual Mt. Pinatubo aerosols, followed by the cleanest stratosphere in decades. As such, the last 13 years of the record reflect changes that have occurred predominantly in the troposphere. The field calibration technique is briefly described and compared to Langley calibrations from Mauna Loa Observatory. A modified cloudscreening technique is introduced that increases the number of daily averaged AODs retrieved annually to about 250 days compared with 175 days when a more conservative method was employed in earlier studies. AODs are calculated when the air mass is less than six; that is, when the Sun’s elevation is greater than 9.25°. The more inclusive cloud screen and the use of most of the daylight hours yield a data set that can be used to more faithfully represent the true aerosol climate for this site. The diurnal aerosol cycle is examined month-by-month to assess the effects of an aerosol climatology on the basis of infrequent sampling such as that from satellites.

14 SOLAR ENERGY↗

Aerosol Direct Radiative Effects at the ARM SGP and TWP Sites: Clear Skies

The clear-sky aerosol direct radiative effect (DRE) was estimated at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) and Tropical Western Pacific (TWP) sites. The NASA Langley Fu-Liou radiation model was used with observed inputs including aerosol vertical extinction profile from the Raman lidar; spectral aerosol optical depth (AOD), single-scattering albedo and asymmetry factor from Aerosol Robotic Network; temperature and water vapor profiles from radiosondes; and surface shortwave (SW) spectral albedo from radiometers. A radiative closure experiment was conducted for clear-sky conditions. The mean differences of modeled and observed surface downwelling SW total fluxes were 1 W m-2 at SGP and 2 W m -2 at TWP, which are within observational uncertainty. At SGP, the estimated annual mean clear-sky aerosol DRE is -3.00 W m -2 at the top of atmosphere (TOA) and -6.85 W m -2 at the surface. The strongest aerosol DRE of -4.81 (-10.77) W m -2 at the TOA (surface) are in the summer when AODs are largest. The weakest aerosol DRE of -.28 (-2.77) W m -2 at the TOA (surface) are in November–January when AODs and single-scattering albedos are lowest. At TWP, the annual mean clear-sky DRE is -2.82 W m-2 at the TOA and -10.34 W m -2 at the surface. The strongest aerosol DRE of -5.95 (-22.20) W m -2 at the TOA (surface) are in November (October) due to the biomass burning season’s peak. The weakest aerosol DRE of -0.96 (-4.16) W m -2 at the TOA (surface) are in March (April) when AODs are smallest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of Ocean Ecosystem on Marine Aerosol‐Cloud Interaction

Using satellite data for the surface ocean, aerosol optical depth (AOD), and cloud microphysical parameters, we show that statistically significant positive correlations exist between ocean ecosystem productivity, the abundance of submicron aerosols, and cloud microphysical properties over different parts of the remote oceans. The correlation coefficient for remotely sensed surface chlorophyll a concentration ([Chl‐ a ]) and liquid cloud effective radii over productive areas of the oceans varies between −0.2 and −0.6. Special attention is given to identifying (and addressing) problems from correlation analysis used in the previous studies that can lead to erroneous conclusions. A new approach (using the difference between retrieved AOD and predicted sea salt aerosol optical depth, AOD diff ) is developed to explore causal links between ocean physical and biological systems and the abundance of cloud condensation nuclei (CCN) in the remote marine atmosphere. We have found that over multiple time periods, 550 nm AOD diff (sensitive to accumulation mode aerosol, which is the prime contributor to CCN) correlates well with [Chl‐ a ] over the productive waters of the Southern Ocean. Since [Chl‐ a ] can be used as a proxy of ocean biological productivity, our analysis demonstrates the role of ocean ecology in contributing CCN, thus shaping the microphysical properties of low‐level marine clouds.

Meskhidze, Nicholas↗

Climatological simulations of ozone and atmospheric aerosols in the Greater Cairo region

An integrated chemistry-climate model (RegCM4-CHEM) simulates present-day climate, ozone and tropospheric aerosols over Egypt with a focus on Greater Cairo (GC) region. The densley populated GC region is known for its severe air quality issues driven by high levels of anthropogenic pollution in conjuction with natural sources such as dust and agricultural burning events. We find that current global emission inventories underestimate key pollutants such as nitrogen oxides and anthropogenic aerosol species. In the GC region, average-ground-based NO2 observations of 40-60 ppb are substantially higher than modeled estimates (5-10 ppb), likely due to model grid resolution, improper boundary layer representation, and poor emissions inventories. Observed ozone concentrations range from 35 ppb (winter) to 80 ppb (summer). The model reproduces the seasonal cycle fairly well, but modeled summer ozone is understimated by approximately 15 ppb and exhibits little interannual variability. For aerosols, springtime dust events dominate the seasonal aerosol cycle. The chemistry-climate model captures the springtime peak aerosol optical depth (AOD) of 0.7-1 but is slightly greater than satellite-derived AOD. Observed AOD decreases in the summer and increases again in the fall due to agricultural burning events in the Nile Delta, yet the model underestimates this fall observed AOD peak, as standard emissions inventories underestimate this burning and the resulting aerosol emissions. Our comparison of modeled gas and particulate phase atmospheric chemistry in the GC region indicates that improved emissions inventories of mobile sources and other anthropogenic activities are needed to improve air quality simulations in this region.

Steiner, A. L.↗

Failure and Redemption of Multifilter Rotating Shadowband Radiometer (MFRSR)/Normal Incidence Multifilter Radiometer (NIMFR) Cloud Screening: Contrasting Algorithm Performance at Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) and Southern Great Plains (SGP) Sites

Well-known cloud-screening algorithms, which are designed to remove cloud-contaminated aerosol optical depths (AOD) from AOD measurements, have shown great performance at many middle-to-low latitude sites around the world. However, they may occasionally fail under challenging observational conditions, such as when the sun is low (near the horizon) or when optically thin clouds with small spatial inhomogeneity occur. Such conditions have been observed quite frequently at the high-latitude Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) sites. A slightly modified cloud-screening version of the standard algorithm is proposed here with a focus on the ARM-supported Multifilter Rotating Shadowband Radiometer (MFRSR) and Normal Incidence Multifilter Radiometer (NIMFR) data. The modified version uses approximately the same techniques as the standard algorithm, but it additionally examines the magnitude of the slant-path line of sight transmittance and eliminates points when the observed magnitude is below a specified threshold. Substantial improvement of the multi-year (1999-2012) aerosol product (AOD and its Angstrom exponent) is shown for the NSA sites when the modified version is applied. Moreover, this version reproduces the AOD product at the ARM Southern Great Plains (SGP) site, which was originally generated by the standard cloud-screening algorithms. The proposed minor modification is easy to implement and its application to existing and future cloud-screening algorithms can be particularly beneficial for challenging observational conditions.

aerosol↗

Modelling of long-range transport of Southeast Asia biomass-burning aerosols to Taiwan and their radiative forcings over East Asia

Biomass burning is a major source of aerosols and air pollutants during the springtime in Southeast Asia. At Lulin mountain background station (elevation 2862 m) in Taiwan, the concentrations of carbon monoxide (CO), ozone (O3) and particulate matter particles with diameter less than 10 μm (PM10), were measured around 150-250 ppb, 40-60 ppb, and 10-30μg/m3, respectively at spring time (February-April) during 2006 and 2009, which are about 2~3 times higher than those in other seasons. Observations and simulation results indicate that the higher concentrations during the spring time are clearly related to biomass burning plumes transported from the Indochina Peninsula of Southeast Asia. The spatial distribution of high aerosols optical depth (AOD) were identified by the satellite measurement and Aerosol Robotic Network (AERONET) ground observation, and could be reasonably captured by the WRF-Chem model during the study period of 15-18 March, 2008. AOD reached as high as 0.8-1.0 in Indochina ranging from 10 to 22°N and 95 to 107°E. Organic carbon (OC) is a major contributor of AOD over Indochina according to simulation results. The contributor of AOD from black carbon (BC) is minor when compared with OC over the Indochina. However, the direct absorption radiative forcing of BC in the atmosphere could reach 35-50 W m-2, which is about 8-10 times higher than that of OC. The belt shape of radiation reduction at surface from Indochina to Taiwan could be as high 20-40 W m-2 during the study period. The implication of the radiative forcing from biomass burning aerosols and their impact on the regional climate in East Asia is our major concern.

aerosols optical depth↗

Assessment of the Effect of Air Pollution Controls on Trends in Shortwave Radiation over the United States from 1995 through 2010 from Multiple Observation Networks

Long term datasets of total (all-sky) and clear-sky downwelling shortwave (SW) radiation, cloud cover fraction (cloudiness) and aerosol optical depth (AOD) are analyzed together with aerosol concentration from several networks (e.g. SURFRAD, CASTNET, IMPROVE and ARM) in the United States (US). Seven states with varying climatology are selected to better understand the effect of aerosols and clouds on SW radiation. This analysis aims to test the hypothesis that the reductions in anthropogenic aerosol burden resulting from substantial reductions in emissions of sulfur dioxide and nitrogen oxides over the past 15 years across the US has caused an increase in surface SW radiation. We show that the total and clear-sky downwelling SW radiation from seven sites have increasing trends except Penn State which shows no tendency in clear-sky SW radiation. After investigating several confounding factors, the causes can be due to the geography of the site, aerosol distribution, heavy air traffic and increasing cloudiness. Moreover, we assess the relationship between total column AOD with surface aerosol concentration to test our hypothesis. In our findings, the trends of clear-sky SW radiation, AOD, and aerosol concentration from the sites in eastern US agree well with our hypothesis. However, the sites in western US demonstrate increasing AOD associated with mostly increasing trends in surface aerosol concentration. At these sites, the changes in aerosol burden and/or direct aerosol effects alone cannot explain the observed changes in SW radiation, but other factors need to be considered such as cloudiness, aerosol vertical profiles and elevated plumes.

1995-2010↗

Source sector and region contributions to BC and PM 2.5 in Central Asia

Particulate matter (PM) mass concentrations, seasonal cycles, source sector, and source region contributions in Central Asia (CA) are analyzed for the period April 2008–July 2009 using the Sulfur Transport and dEposition Model (STEM) chemical transport model and modeled meteorology from the Weather Research and Forecasting (WRF) model. Predicted aerosol optical depth (AOD) values (annual mean value ~0.2) in CA vary seasonally, with lowest values in the winter. Surface PM 2.5 concentrations (annual mean value ~10 μg m -3 ) also exhibit a seasonal cycle, with peak values and largest variability in the spring/summer, and lowest values and variability in the winter (hourly values from 2 to 90 μg m -3 ). Surface concentrations of black carbon (BC) (mean value ~0.1 μg m -3 ) show peak values in the winter. The simulated values are compared to surface measurements of AOD as well as PM 2.5 , PM 10 , BC, and organic carbon (OC) mass concentrations at two regional sites in Kyrgyzstan (Lidar Station Teplokluchenka (LST) and Bishkek). The predicted values of AOD and PM mass concentrations and their seasonal cycles are fairly well captured. The carbonaceous aerosols are underpredicted in winter, and analysis suggests that the winter heating emissions are underestimated in the current inventory. Dust, from sources within and outside CA, is a significant component of the PM mass and drives the seasonal cycles of PM and AOD. On an annual basis, the power and industrial sectors are found to be the most important contributors to the anthropogenic portion of PM 2.5 . Residential combustion and transportation are shown to be the most important sectors for BC. Biomass burning within and outside the region also contributes to elevated PM and BC concentrations. The analysis of the transport pathways and the variations in particulate matter mass and composition in CA demonstrates that this region is strategically located to characterize regional and intercontinental transport of pollutants. Aerosols at these sites are shown to reflect dust, biomass burning, and anthropogenic sources from Europe; South, East, and Central Asia; and Russia depending on the time period. Simulations for a reference 2030 emission scenario based on pollution abatement measures already committed to in current legislation show that PM 2.5 and BC concentrations in the region increase, with BC growing more than PM 2.5 on a relative basis. This suggests that both the health impacts and the climate warming associated with these particles may increase over the next decades unless additional control measures are taken. The importance of observations in CA to help characterize the changes that are rapidly taking place in the region are discussed.

54 ENVIRONMENTAL SCIENCES↗

Forecasting the northern African dust outbreak towards Europe in April 2011: A model intercomparison

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. In this paper, our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

54 ENVIRONMENTAL SCIENCES↗

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2 , respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.

54 ENVIRONMENTAL SCIENCES↗