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NASA NTRS2012

Global Long-Term SeaWiFS Deep Blue Aerosol Products available at NASA GES DISC

Long-term climate data records about aerosols are needed in order to improve understanding of air quality, radiative forcing, and for many other applications. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a global well-calibrated 13- year (1997-2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). Recently, global aerosol products derived from SeaWiFS with Deep Blue algorithm (SWDB) have become available for the entire mission, as part of the NASA Making Earth Science data records for Use in Research for Earth Science (MEaSUREs) program. The latest Deep Blue algorithm retrieves aerosol properties not only over bright desert surfaces, but also vegetated surfaces, oceans, and inland water bodies. Comparisons with AERONET observations have shown that the data are suitable for quantitative scientific use [1],[2]. The resolution of Level 2 pixels is 13.5x13.5 km2 at the center of the swath. Level 3 daily and monthly data are composed by using best quality level 2 pixels at resolution of both 0.5ox0.5o and 1.0ox1.0o. Focusing on the southwest Asia region, this presentation shows seasonal variations of AOD, and the result of comparisons of 5-years (2003- 2007) of AOD from SWDB (Version 3) and MODIS Aqua (Version 5.1) for Dark Target (MYD-DT) and Deep Blue (MYD-DB) algorithms.

Shen, Suhung↗
NASA NTRS2013

MODIS 3km Aerosol Product: Algorithm and Global Perspective

After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.

Remer, L. A.↗
NASA NTRS2012

Variability and Trends of Aerosol Properties over Kanpur, Northern India using AERONET Data (2001-10)

Natural and anthropogenic aerosols over northern India play an important role in influencing the regional radiation budget, causing climate implications to the overall hydrological cycle of South Asia. In the context of regional climate change and air quality, we discuss aerosol loading variability and trends at Kanpur AERONET station located in the central part of the Indo-Gangetic plains (IGP), during the last decade (2001-10). Ground-based radiometric measurements show an overall increase in column-integrated aerosol optical depth (AOD) on a yearly basis. This upward trend is mainly due to a sustained increase in the seasonal/monthly averaged AOD during the winter (Dec-Feb) and post-monsoon (Oct-Nov) seasons (dominated by anthropogenic emissions). In contrast, a neutral to weak declining trend is observed during late pre-monsoon (Mar-May) and monsoon (Jun-Sep) months, mainly influenced by inter-annual variations of dust outbreaks. A general decrease in coarse-mode aerosols associated with variable dust activity is observed, whereas the statistically significant increasing post-monsoon/winter AOD is reflected in a shift of the columnar size distribution towards relatively larger particles in the accumulation mode. Overall, the present study provides an insight into the pronounced seasonal behavior in aerosol loading trends and, in general, is in agreement with that associating the findings with those recently reported by satellite observations (MODIS and MISR) over northern India. Our results further suggest that anthropogenic emissions (due mainly to fossil-fuel and biomass combustion) over the IGP have continued to increase in the last decade.

AERONET↗
NASA NTRS2012

Intercomparison of Desert Dust Optical Depth from Satellite Measurements

This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify the differences between current datasets. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as assumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, it is important to note that differences in sampling, related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset can be an important issue.

desert dust↗
NASA NTRS2013

Estimating the Direct Radiative Effect of Absorbing Aerosols Overlying Marine Boundary Layer Clouds in the Southeast Atlantic Using MODIS and CALIOP

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

aerosols↗
NASA NTRS2012

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

MODIS aerosol retrievals↗
NASA NTRS2014

Multi-Decadal Aerosol Variations from 1980 to 2009: A Perspective from Observations and a Global Model

Aerosol variations and trends over different land and ocean regions during 1980-2009 are analyzed with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and observations from multiple satellite sensors and ground-based networks. Excluding time periods with large volcanic influences, the tendency of aerosol optical depth (AOD) and surface concentration over polluted land regions is consistent with the anthropogenic emission changes.The largest reduction occurs over Europe, and regions in North America and Russia also exhibit reductions. On the other hand, East Asia and South Asia show AOD increases, although relatively large amount of natural aerosols in Asia makes the total changes less directly connected to the pollutant emission trends. Over major dust source regions, model analysis indicates that the dust emissions over the Sahara and Sahel respond mainly to the near-surface wind speed, but over Central Asia they are largely influenced by ground wetness. The decreasing dust trend in the tropical North Atlantic is most closely associated with the decrease of Sahel dust emission and increase of precipitation over the tropical North Atlantic, likely driven by the sea surface temperature increase. Despite significant regional trends, the model-calculated global annual average AOD shows little changes over land and ocean in the past three decades, because opposite trends in different regions cancel each other in the global average. This highlights the need for regional-scale aerosol assessment, as the global average value conceals regional changes, and thus is not sufficient for assessing changes in aerosol loading.

atmopheric aerosols↗
NASA NTRS2014

Simultaneous Retrieval of Aerosol Properties and Clear-Sky Direct Radiative Effect Over the Global Ocean from MODIS

A unified satellite algorithm is presented to simultaneously retrieve aerosol properties (aerosol optical depth; AOD and aerosol type) and clear-sky shortwave direct radiative effect (hereafter, DREA) over ocean. The algorithm is applied to Moderate Resolution Imaging spectroradiometer (MODIS) observations for a period from 2003 to 2010 to assess the DREA over the global ocean. The simultaneous retrieval utilizes lookup table (LUT) containing both spectral reflectances and solar irradiances calculated using a single radiative transfer model with the same aerosol input data. This study finds that aerosols cool the top-of-atmosphere (TOA) and bottom-of-atmosphere (BOA) by 5.2 +/- 0.5 W/sq m and 8.3 W/sq m, respectively, and correspondingly warm the atmosphere (hereafter, ATM) by 3.1 W/sq m. These quantities, solely based on the MODIS observations, are consistent with those of previous studies incorporating chemical transport model simulations and satellite observations. However, the DREAs at BOA and ATM are expected to be less accurate compared to that of TOA due to low sensitivity in retrieving aerosol type information, which is related with the atmospheric heating by aerosols, particularly in low AOD conditions; consequently, the uncertainties could not be quantified. Despite the issue in the aerosol type information, the present method allows us to confine the DREA attributed only to fine-mode dominant aerosols, which are expected to be mostly anthropogenic origin, in the range from 1.1 W/sq m to 1.3 W/sq m at TOA. Improvements in size-resolved AOD and SSA retrievals from current and upcoming satellite instruments are suggested to better assess the DREA, particularly at BOA and ATM, where aerosol absorptivity induces substantial uncertainty.

MODIS↗
NASA NTRS2012

Characterization of Aerosols over the Indochina Peninsula from Satellite-Surface Observations During Biomass Burning Pre-Monsoon Season

This paper presents characterization of aerosols over the Indochina peninsular regions of Southeast Asia during pre-monsoon season from satellite and ground-based radiometric observations. Our analysis focuses on the seasonal peak period in aerosol loading and biomass burning, prior to the onset of the Asian summer monsoon, as observed in the inter-annual variations of Aerosol Optical Depth (AOD) and fire count data from MODIS. Multi-year (2007-2011) analysis of spaceborne lidar measurements, from CALIOP, indicates presence of aerosols mostly within boundary layer, however extending to elevated altitudes to approx. 4 km over northern regions of Indochina, encompassing Myanmar, northern Thailand and southern China. In addition, a strong gradient in aerosol loading and vertical distribution is observed from the relatively clean equatorial conditions to heavy smoke-laden northern regions (greater aerosol extinction and smaller depolarization ratio). Based on column-integrated ground-based measurements from four AERONET locations distributed over Thailand, the regional aerosol loading is found to be significantly absorbing with spectral single scattering albedo (SSA) below 0.91+/-0.02 in the 440-1020 nm range, with lowest seasonal mean SSA (most absorbing aerosol) over the northern location of Chiang Mai (SSA approx. 0.85) during pre-monsoon season. The smoke-laden aerosol loading is found to exhibit a significant diurnal pattern with higher AOD departures during early morning observations relative to late afternoon conditions (peak difference of more than 15% amplitude). Finally, satellite-based aerosol radiative impact is assessed using CERES shortwave Top-of-Atmosphere flux, in conjunction with MODIS AOD. Overall, a consistency in the aerosol-induced solar absorption characteristic is found among selected regions from ground-based sunphotometer-derived spectral SSA retrievals and satellite-based radiative forcing analysis.

Indochina↗
NASA NTRS2014

Development and Testing of the New Surface LER Climatology for OMI UV Aerosol Retrievals

Ozone Monitoring Instrument (OMI) onboard Aura satellite retrieved aerosols properties using UV part of solar spectrum. The OMI near UV aerosol algorithm (OMAERUV) is a global inversion scheme which retrieves aerosol properties both over ocean and land. The current version of the algorithm makes use of TOMS derived Lambertian Equivalent Reflectance (LER) climatology. A new monthly climatology of surface LER at 354 and 388 nm have been developed. This will replace TOMS LER (380 nm and 354nm) climatology in OMI near UV aerosol retrieval algorithm. The main objectives of this study is to produce high resolution (quarter degree) surface LER sets as compared to existing one degree TOMS surface LERs, to product instrument and wavelength consistent surface climatology. Nine years of OMI observations have been used to derive monthly climatology of surface LER. MODIS derived aerosol optical depth (AOD) have been used to make aerosol corrections on OMI wavelengths. MODIS derived BRDF adjusted reflectance product has been also used to capture seasonal changes in the surface characteristics. Finally spatial and temporal averaging techniques have been used to fill the gaps around the globes, especially in the regions with consistent cloud cover such as Amazon. After implementation of new surface data in the research version of algorithm, comparisons of AOD and single scattering albedo (SSA) have been performed over global AERONET sites for year 2007. Preliminary results shows improvements in AOD retrievals globally but more significance improvement were observed over desert and bright locations. We will present methodology of deriving surface data sets and will discuss the observed changes in retrieved aerosol properties with respect to reference AERONET measurements.

Aerosol↗
NASA NTRS2014

Aerosol Seasonal Variations over Urban-Industrial Regions in Ukraine According to AERONET and POLDER Measurements

The paper presents an investigation of aerosol seasonal variations in several urban-industrial regions in Ukraine. Our analysis of seasonal variations of optical and physical aerosol parameters is based on the sun-photometer 2008-2013 data from two urban ground-based AERONET (AErosol RObotic NETwork) sites in Ukraine (Kyiv, Lugansk) as well as on satellite POLDER instrument data for urban-industrial areas in Ukraine. We also analyzed the data from one AERONET site in Belarus (Minsk) in order to compare with the Ukrainian sites. Aerosol amount and optical depth (AOD) values in the atmosphere columns over the large urbanized areas like Kyiv and Minsk have maximum values in the spring (April-May) and late summer (August), whereas minimum values are observed in late autumn. The results show that fine-mode particles are most frequently detected during the spring and late summer seasons. The analysis of the seasonal AOD variations over the urban-industrial areas in the eastern and central parts of Ukraine according to both ground-based and POLDER data exhibits the similar traits. The seasonal variation similarity in the regions denotes the resemblance in basic aerosol sources that are closely related to properties of aerosol particles. The behavior of basic aerosol parameters in the western part of Ukraine is different from eastern and central regions and shows an earlier appearance of the spring and summer AOD maxima. Spectral single-scattering albedo, complex refractive index and size distribution of aerosol particles in the atmosphere column over Kyiv have different behavior for warm (April-October) and cold seasons. The seasonal features of fine and coarse aerosol particle behavior over the Kyiv site were analyzed. A prevailing influence of the fine-mode particles on the optical properties of the aerosol layer over the region has been established. The back-trajectory and cluster analysis techniques were applied to study the seasonal back trajectories and prevailing directions of the arrived air mass for the Kyiv and Minsk sites.

Ukraine↗
NASA NTRS2015

Comparison of GFED3, QFED2 and FEER1 Biomass Burning Emissions Datasets in a Global Model

Biomass burning contributes about 40% of the global loading of carbonaceous aerosols, significantly affecting air quality and the climate system by modulating solar radiation and cloud properties. However, fire emissions are poorly constrained in models on global and regional levels. In this study, we investigate 3 global biomass burning emission datasets in NASA GEOS5, namely: (1) GFEDv3.1 (Global Fire Emissions Database version 3.1); (2) QFEDv2.4 (Quick Fire Emissions Dataset version 2.4); (3) FEERv1 (Fire Energetics and Emissions Research version 1.0). The simulated aerosol optical depth (AOD), absorption AOD (AAOD), angstrom exponent and surface concentrations of aerosol plumes dominated by fire emissions are evaluated and compared to MODIS, OMI, AERONET, and IMPROVE data over different regions. In general, the spatial patterns of biomass burning emissions from these inventories are similar, although the strength of the emissions can be noticeably different. The emissions estimates from QFED are generally larger than those of FEER, which are in turn larger than those of GFED. AOD simulated with all these 3 databases are lower than the corresponding observations in Southern Africa and South America, two of the major biomass burning regions in the world.

biomass burning↗
NASA NTRS2015

Nighttime Aerosol Optical Depth Measurements Using a Ground-based Lunar Photometer

In recent years it was proposed to combine AERONET network photometer capabilities with a high precision lunar model used for satellite calibration to retrieve columnar nighttime AODs. The USGS lunar model can continuously provide pre-atmosphere high precision lunar irradiance determinations for multiple wavelengths at ground sensor locations. When combined with measured irradiances from a ground-based AERONET photometer, atmospheric column transmissions can determined yielding nighttime column aerosol AOD and Angstrom coefficients. Additional demonstrations have utilized this approach to further develop calibration methods and to obtain data in polar regions where extended periods of darkness occur. This new capability enables more complete studies of the diurnal behavior of aerosols, and feedback for models and satellite retrievals for the nighttime behavior of aerosols. It is anticipated that the nighttime capability of these sensors will be useful for comparisons with satellite lidars such as CALIOP and CATS in additional to ground-based lidars in MPLNET at night, when the signal-to-noise ratio is higher than daytime and more precise AOD comparisons can be made.

Berkoff, Tim↗
NASA NTRS2016

Combing Visible and Infrared Spectral Tests for Dust Identification

The MODIS Dark Target aerosol algorithm over Ocean (DT-O) uses spectral reflectance in the visible, near-IR and SWIR wavelengths to determine aerosol optical depth (AOD) and Angstrom Exponent (AE). Even though DT-O does have "dust-like" models to choose from, dust is not identified a priori before inversion. The "dust-like" models are not true "dust models" as they are spherical and do not have enough absorption at short wavelengths, so retrieved AOD and AE for dusty regions tends to be biased. The inference of "dust" is based on postprocessing criteria for AOD and AE by users. Dust aerosol has known spectral signatures in the near-UV (Deep blue), visible, and thermal infrared (TIR) wavelength regions. Multiple dust detection algorithms have been developed over the years with varying detection capabilities. Here, we test a few of these dust detection algorithms, to determine whether they can be useful to help inform the choices made by the DT-O algorithm. We evaluate the following methods: The multichannel imager (MCI) algorithm uses spectral threshold tests in (0.47, 0.64, 0.86, 1.38, 2.26, 3.9, 11.0, 12.0 micrometer) channels and spatial uniformity test [Zhao et al., 2010]. The NOAA dust aerosol index (DAI) uses spectral contrast in the blue channels (412nm and 440nm) [Ciren and Kundragunta, 2014]. The MCI is already included as tests within the "Wisconsin" (MOD35) Cloud mask algorithm.

aerosol optical depth↗
NASA NTRS2016

Satellite Maps and Relevant Compositional Properties of PM2.5 in Difficult Winter Situations and Comparisons to DISCOVER-AQ Airborne Sampling

Mediterranean-climate regions like California's San Joaquin Valley are subject to severe wintertime particulate pollution affecting public health. We present maps of episodes and particulate diagnostics to aid diagnosis and amelioration. For abatement at sources, we require an understanding of sources and transport. Remote sensing should be of aid, but radiance-to-particle relationships are far different from methods which have been of use in the Eastern USA, Northern and Central Europe. Here are the problems: (a) Thin if very polluted mixed layers (MLs) yield optical depths, AOD, near the detection level, (b) bright and quite variegated surfaces (c) Unusual particle composition (e.g., predominance of NH4NO3 and fireplace buning aerosol), which complicate the relationship of AOD to PM2.5. Specialized analysis of MODIS-Aqua data to obtain AOD using the multi-angle (MAIAC) technique employed by Lyapustin and Wang. Meteorological analyses like NOAA's Rapid Analysis Product (RAP, or newer products like HRRR), which are formulated to remain close to observations (e.g. of water), provide useful ML information corroborated by DISCOVER-AQ in-situ and lidar observations. The many PM2.5 measurements allow a calibration of these products and thus maps of aerosol on many successive aerosol buildups. These calibrations also allow insight into compositional information relevant to MODIS retrievals, the product of aerosol density and specific scattering. We have found that the rich in-situ, lidar, and sun-photometer data sets of NASA'S DISCOVER-AQ data set (2013) of great aid. We will highlight the most interesting of many intercomparisons possible with this rich data set. We conclude with a description of new work to extend these insights to similar regions, e.g. the Imperial Valley of California, the Po Valley and maritime Southern Europe, and the litoral regions of Israel.

aerosols↗
NASA NTRS2016

Response of SO2 and Particulate Air Pollution to Local and Regional Emission Controls: A Case Study in Maryland

This paper addresses the questions of what effect local regulations can have on pollutants with different lifetimes and how surface observations and remotely sensed data can be used to determine the impacts. We investigated the decadal trends of tropospheric sulfur dioxide (SO2) and aerosol pollution over Maryland and its surrounding states, using surface, aircraft, and satellite measurements. Aircraft measurements indicated fewer isolated SO2 plumes observed in summers, a 40 decrease of column SO2, and a 20 decrease of atmospheric optical depth (AOD) over Maryland after the implementation of local regulations on sulfur emissions from power plants (90 reduction from 2010). Surface observations of SO2 and particulate matter (PM) concentrations in Maryland show similar trends. OMI SO2 and MODIS AOD observations were used to investigate the column contents of air pollutants over the eastern U.S.; these indicate decreasing trends in column SO2 (60 decrease) and AOD (20 decrease). The decrease of upwind SO2 emissions also reduced aerosol loadings over the downwind Atlantic Ocean near the coast by 20, while indiscernible changes of the SO2 column were observed. A step change of SO2 emissions in Maryland starting in 20092010 had an immediate and profound benefit in terms of local surface SO2 concentrations but a modest impact on aerosol pollution, indicating that short-lived pollutants are effectively controlled locally, while long-lived pollutants require regional measures.

satellite measurements↗
NASA NTRS2016

Natural and Anthropogenic Aerosol Trends from Satellite and Surface Observations and Model Simulations over the North Atlantic Ocean from 2002 to 2012

Aerosols contribute to Earths radiative budget both directly and indirectly, and large uncertainties remain in quantifying aerosol effects on climate. Variability in aerosol distribution and properties, as might result from changing emissions and transport processes, must be characterized. In this study, variations in aerosol loading across the eastern seaboard of theUnited States and theNorthAtlanticOcean during 2002 to 2012 are analyzed to examine the impacts of anthropogenic emission control measures using monthly mean data from MODIS, AERONET, and IMPROVE observations and Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulation.MODIS observes a statistically significant negative trend in aerosol optical depth (AOD) over the midlatitudes (-0.030 decade(sup-1)). Correlation analyses with surface AOD from AERONET sites in the upwind region combined with trend analysis from GOCART component AOD confirm that the observed decrease in the midlatitudes is chiefly associated with anthropogenic aerosols that exhibit significant negative trends from the eastern U.S. coast extending over the western North Atlantic. Additional analysis of IMPROVE surface PM(sub 2.5) observations demonstrates statistically significant negative trends in the anthropogenic components with decreasing mass concentrations over the eastern United States. Finally, a seasonal analysis of observational datasets is performed. The negative trend seen by MODIS is strongest during spring (MAM) and summer (JJA) months. This is supported by AERONET seasonal trends and is identified from IMPROVE seasonal trends as resulting from ammonium sulfate decreases during these seasons.

Jongeward, Andrew R.↗
NASA NTRS2015

Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011

Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

PM2.5↗