Total Column Aerosol Optical Depth Research Articles

Ground solar absorption observations of total column CO, CO2, CH4, and aerosol optical depth from California's Sequoia Lightning Complex Fire: emission factors and modified combustion efficiency at regional scales

Abstract. With global wildfires becoming more widespread and severe, tracking their emissions of greenhouse gases and air pollutants is becoming increasingly important. Wildfire emissions have primarily been characterized by in situ laboratory and field observations at fine scales. While this approach captures the mechanisms relating emissions to combustion phase and fuel properties, their evaluation on regional-scale plumes has been limited. In this study, we report remote observations of total column trace gases and aerosols during the 2020 wildfire season from smoke plumes in the Sierra Nevada of California with an EM27/SUN solar Fourier transform infrared (FTIR) spectrometer. We derive total column aerosol optical depth (AOD), emission factors (EFs) and modified combustion efficiency (MCE) for these fires and evaluate relationships between them, based on combustion phase at regional scales. We demonstrate that the EM27/SUN effectively detects changes in CO, CO2, and CH4 in the atmospheric column at ∼10 km horizontal scales that are attributed to wildfire emissions. These observations are used to derive total column EFCO of 120.5±12.2 and EFCH4 of 4.3±0.8 for a regional smoke plume event in mixed combustion phases. These values are consistent with in situ relationships measured in similar temperate coniferous forest wildfires. FTIR-derived AOD was compared to a nearby AERONET (AErosol RObotic NETwork) station and observed ratios of XCO to AOD were consistent with those previously observed from satellites. We also show that co-located XCO observations from the TROPOspheric Monitoring Instrument (TROPOMI) satellite-based instrument are 9.7±1.3 % higher than our EM27/SUN observations during the wildfire period. Finally, we put wildfire CH4 emissions in context of the California state CH4 budget and estimate that 213.7±49.8 Gg CH4 were emitted by large wildfires in California during 2020, about 13.7 % of the total state CH4 emissions in 2020. Our work demonstrates a novel application of the ground-based EM27/SUN solar spectrometers in wildfire monitoring by integrating regional-scale measurements of trace gases and aerosols from smoke plumes.

Airborne HSRL-2 measurements of elevated aerosol depolarization associated with non-spherical sea salt

Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA Earth Venture Suborbital-3 (EVS-3) Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed elevated particulate linear depolarization associated with aerosols within the marine boundary layer. These observations were acquired off the east coast of the United States during both winter and summer 2020 and 2021 when the HSRL-2 was deployed on the NASA LaRC King Air aircraft. During 20 of 63 total flight days, particularly on days with cold air outbreaks, linear particulate depolarization at 532 nm exceeded 0.15–0.20 within the lowest several hundred meters of the atmosphere, indicating that these particles were non-spherical. Higher values of linear depolarization typically were measured at 355 nm and lower values were measured at 1,064 nm. Several lines of evidence suggest that these non-spherical particles were sea salt including aerosol extinction/backscatter ratio (“lidar ratio”) values of 20–25 sr measured at both 355 and 532 nm by the HSRL-2, higher values of particulate depolarization measured at low (< 60%) relative humidity, coincident airbornein situsize and composition measurements, and aerosol transport simulations. The elevated aerosol depolarization values were not correlated with wind speed but were correlated with salt mass fraction and effective radius of the aerosol when the relative humidity was below 60%. HSRL-2 measured median particulate extinction values of about 20 Mm−1 at 532 nm associated with these non-spherical sea salt particles and found that the aerosol optical depth (AOD) contributed by these particles remained small (0.03–0.04) but represented on average about 30%–40% of the total column AOD. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) spaceborne lidar aerosol measurements during several cold air outbreaks and CALIOP retrievals of column aerosol lidar ratio using column AOD constraints suggest that CALIOP operational aerosol algorithms can misclassify these aerosols as dusty marine rather than marine aerosols. Such misclassification leads to ∼40–50% overestimates in the assumed lidar ratio and in subsequent retrievals of aerosol optical depth and aerosol extinction.

Obtaining vertical distribution of PM2.5 from CALIOP data and machine learning algorithms

Aerosol optical depth (AOD) has been widely used to estimate the near-surface PM2.5 (fine particulate matter with particle size less than 2.5 μm). However, the total-column AOD obtained by passive remote sensing instruments can neither distinguish the contribution of AOD in various altitude layers nor obtain the vertical PM2.5 concentration. In this study, we compared several AOD-PM2.5 models including Extra Trees (ET), Random Forest (RF), Deep Neural Network (DNN), and Gradient Boosting Regression Tree (GBRT), and analyzed the corresponding results using AOD of different altitudes and auxiliary data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The results indicate that the ET model performs best in terms of the model effectiveness and feature interpretation on the training dataset. We conclude that the feature importance of the bottom layer AOD is higher than that of the upper and total column AOD. The results showed that regional differences existed in the optimal height of the AOD-PM2.5 correlation in study area. The results of cross-validation indicate that ET manages the most appealing overall performance with an R2 (RMSE) of 0.85 (17.77 μg/m3). Regarding the 729 sites involved in this study, 73% had R2 > 0.7, and the region or season with higher AOD feature importance achieves better model performance. The results of the AOD-PM2.5 model in each layer were corrected using the AOD weight, to obtained the PM2.5 vertical concentrations from 2015 to 2019. The results highlight that the high PM2.5 concentration area is primarily near the ground and decreases with height. Additionally, the PM2.5 vertical concentration in Beijing-Tianjin-Hebei (−1.80 μg/m3, P < 0.001), Central China (−1.62 μg/m3, P < 0.001), and Pearl River Delta (−0.66 μg/m3, P < 0.001) show an apparent downward trend. We believe that the vertical distribution analysis of PM2.5 can provide meaningful information for studying air pollution.

Fine Particle Exposure and Clinical Aggravation in Neurodegenerative Diseases in New York State.

Background:Adult-onset neurodegenerative diseases affect millions and negatively impact health care systems worldwide. Evidence suggests that air pollution may contribute to aggravation of neurodegeneration, but studies have been limited.Objective:We examined the potential association between long-term exposure to particulate matter in aerodynamic diameter [fine particulate matter ()] and disease aggravation in Alzheimer’s (AD) and Parkinson’s (PD) diseases and amyotrophic lateral sclerosis (ALS), using first hospitalization as a surrogate of clinical aggravation.Methods:We used data from the New York Department of Health Statewide Planning and Research Cooperative System (SPARCS 2000–2014) to construct annual county counts of first hospitalizations with a diagnosis of AD, PD, or ALS (total, urbanicity-, sex-, and age-stratified). We used annual concentrations estimated by a prediction model at a resolution, which we aggregated to population-weighted county averages to assign exposure to cases based on county of residence. We used outcome-specific mixed quasi-Poisson models with county-specific random intercepts to estimate rate ratios (RRs) for a 1-y exposure. We allowed for nonlinear exposure–outcome relationships using penalized splines and accounted for potential confounders.Results:We found a positive nonlinear association that plateaued above (, 95% CI: 1.04, 1.14 for a increase from 8.1 to ). We also found a linear positive association (, 95% CI: 1.01, 1.09 per increase), and suggestive evidence of an association with AD. We found effect modification by age for PD and ALS with a stronger positive association in patients of age but found insufficient evidence of effect modification by sex or urbanization level for any of the outcomes.Conclusion:Our findings suggest that annual increase in county-level concentrations may contribute to clinical aggravation of PD and ALS. Importantly, the average annual concentration in our study was , below the current American national standards, suggesting the standards may not adequately protect the aging population. https://doi.org/10.1289/EHP7425

New in situ aerosol hyperspectral optical measurements over 300–700 nm – Part 1: Spectral Aerosol Extinction (SpEx) instrument field validation during the KORUS-OC cruise

Abstract. In situ observations of spectrally resolved aerosol extinction coefficients (300–700 nm at ∼ 0.8 nm resolution) from the May–June 2016 Korea–United States Ocean Color (KORUS-OC) oceanographic field campaign are reported. Measurements were made with the custom-built Spectral Aerosol Extinction (SpEx) instrument that previously has been characterized only using laboratory-generated aerosols of known size and composition. Here, the performance of SpEx under realistic operating conditions in the field was assessed by comparison to extinction coefficients derived from commercial instruments that measured scattering and filter-based absorption coefficients at three discrete visible wavelengths. Good agreement was found between these two sets of extinction coefficients with slopes near unity for all three wavelengths within the SpEx measurement error (± 5 Mm−1). The meteorological conditions encountered during the cruise fostered diverse ambient aerosol populations with varying sizes and composition at concentrations spanning 2 orders of magnitude. The sampling inlet had a 50 % size cut of 1.3 µm diameter particles such that the in situ aerosol sampling suite deployed aboard ship measured fine-mode aerosols only. The extensive hyperspectral extinction data set acquired revealed that nearly all measured spectra exhibited curvature in logarithmic space, such that Ångström exponent (α) power law fits could lead to large errors compared to measured values. This problem was particularly acute for α values calculated over only visible wavelengths and then extrapolated to the UV, highlighting the need for measurements in this wavelength range. Second-order polynomial fits to the logarithmically transformed data provided a much better fit to the measured spectra than the linear fits of power laws. Building on previous studies that used total column aerosol optical depth observations to examine the information content of spectral curvature, the relationship between α and the second-order polynomial fit coefficients (a1 and a2) was found to depend on the wavelength range of the spectral measurement such that any given α maps into a line in (a1, a2) coefficient space with a slope of −2LN(λch), where λch is defined as the single wavelength that characterizes the wavelength range of the measured spectrum (i.e., the “characteristic wavelength”). Since the curvature coefficient values depend on λch, it must be taken into account when comparing values from spectra obtained from measurement techniques with different λch. Previously published work has shown that different bimodal size distributions of aerosols can exhibit the same α yet have differing spectral curvature with different (a1, a2). This implies that (a1, a2) contain more information about size distributions than α alone. Aerosol size distributions were not measured during KORUS-OC, and the data reported here were limited to the fine fraction, but the (a1, a2) maps obtained from the SpEx data set are consistent with the expectation that (a1, a2) may contain more information than α – a result that will be explored further with future SpEx and size distribution data sets.

Potential Approach for Single-Peak Extinction Fitting of Aerosol Profiles Based on In Situ Measurements for the Improvement of Surface PM2.5 Retrieval from Satellite AOD Product

The vertical distribution of aerosols is important for accurate surface PM2.5 retrieval and initial modeling forecasts of air pollution, but the observation of aerosol profiles on the regional scale is usually limited. Therefore, in this study, an approach to aerosol extinction profile fitting is proposed to improve surface PM2.5 retrieval from satellite observations. Owing to the high similarity of the single-peak extinction profile in the distribution pattern, the log-normal distribution is explored for the fitting model based on a decadal dataset (3248 in total) from Micro Pulse LiDAR (MPL) measurements. The logarithmic mean, standard deviation, and the height of peak extinction near-surface (Mode) are manually derived as the references for model construction. Considering the seasonal impacts on the planetary boundary layer height (PBLH), Mode, and the height of the surface layer, the extinction profile is then constructed in terms of the planetary boundary layer height (PBLH) and the total column aerosol optical depth (AOD). A comparison between fitted profiles and in situ measurements showed a high level of consistency in terms of the correlation coefficient (0.8973) and root-mean-square error (0.0415). The satellite AOD is subsequently applied for three-dimensional aerosol extinction, and the good agreement of the extinction coefficient with the PM2.5 within the surface layer indicates the good performance of the proposed fitting approach and the potential of satellite observations for providing accurate PM2.5 data on a regional scale.

Using Multi-Angle Imaging SpectroRadiometer Aerosol Mixture Properties for Air Quality Assessment in Mongolia

Ulaanbaatar (UB), the capital city of Mongolia, has extremely poor wintertime air quality with fine particulate matter concentrations frequently exceeding 500 μg/m3, over 20 times the daily maximum guideline set by the World Health Organization. Intensive use of sulfur-rich coal for heating and cooking coupled with an atmospheric inversion amplified by the mid-continental Siberian anticyclone drive these high levels of air pollution. Ground-based air quality monitoring in Mongolia is sparse, making use of satellite observations of aerosol optical depth (AOD) instrumental for characterizing air pollution in the region. We harnessed data from the Multi-angle Imaging SpectroRadiometer (MISR) Version 23 (V23) aerosol product, which provides total column AOD and component-particle optical properties for 74 different aerosol mixtures at 4.4 km spatial resolution globally. To test the performance of the V23 product over Mongolia, we compared values of MISR AOD with spatially and temporally matched AOD from the Dalanzadgad AERONET site and find good agreement (correlation r = 0.845, and root-mean-square deviation RMSD = 0.071). Over UB, exploratory principal component analysis indicates that the 74 MISR AOD mixture profiles consisted primarily of small, spherical, non-absorbing aerosols in the wintertime, and contributions from medium and large dust particles in the summertime. Comparing several machine learning methods for relating the 74 MISR mixtures to ground-level pollutants, including particulate matter with aerodynamic diameters smaller than 2.5 μm ( PM 2.5 ) and 10 μm ( PM 10 ), as well as sulfur dioxide ( SO 2 ), a proxy for sulfate particles, we find that Support Vector Machine regression consistently has the highest predictive performance with median test R 2 for PM 2.5 , PM 10 , and SO 2 equal to 0.461, 0.063, and 0.508, respectively. These results indicate that the high-dimensional MISR AOD mixture set can provide reliable predictions of air pollution and can distinguish dominant particle types in the UB region.

Constraining chemical transport PM2.5 modeling outputs using surface monitor measurements and satellite retrievals: application over the San Joaquin Valley.

Advances in satellite retrieval of aerosol type can improve the accuracy of near-surface air quality characterization by providing broad regional context and decreasing metric uncertainties and errors. The frequent, spatially extensive and radiometrically consistent instantaneous constraints can be especially useful in areas away from ground monitors and progressively downwind of emission sources. We present a physical approach to constraining regional-scale estimates of PM2.5, its major chemical component species estimates, and related uncertainty estimates of chemical transport model (CTM; e.g., the Community Multi-scale Air Quality Model) outputs. This approach uses ground-based monitors where available, combined with aerosol optical depth and qualitative constraints on aerosol size, shape, and light-absorption properties from the Multi-angle Imaging SpectroRadiometer (MISR) on the NASA Earth Observing System’s Terra satellite. The CTM complements these data by providing complete spatial and temporal coverage. Unlike widely used approaches that train statistical regression models, the technique developed here leverages CTM physical constraints such as the conservation of aerosol mass and meteorological consistency, independent of observations. The CTM also aids in identifying relationships between observed species concentrations and emission sources.Aerosol air mass types over populated regions of central California are characterized using satellite data acquired during the 2013 San Joaquin field deployment of the NASA Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) project. We investigate the optimal application of incorporating 275 m horizontal-resolution aerosol air-mass-type maps and total-column aerosol optical depth from the MISR Research Aerosol retrieval algorithm (RA) into regional-scale CTM output. The impact on surface PM2.5 fields progressively downwind of large single sources is evaluated using contemporaneous surface observations. Spatiotemporal R2 and RMSE values for the model, constrained by both satellite and surface monitor measurements based on 10-fold cross-validation, are 0.79 and 0.33 for PM2.5, 0.88 and 0.65 for NO3-, 0.78 and 0.23 for SO42-, and 1.01 for NH+, 0.73 and 0.23 for OC, and 0.31 and 0.65 for EC, respectively. Regional cross-validation temporal and spatiotemporal R2 results for the satellite-based PM2.5 improve by 30 % and 13 %, respectively, in comparison to unconstrained CTM simulations and provide finer spatial resolution. SO42- cross-validation values showed the largest spatial and spatiotemporal R2 improvement, with a 43 % increase. Assessing this physical technique in a well- instrumented region opens the possibility of applying it globally, especially over areas where surface air quality measurements are scarce or entirely absent.

NU-WRF Aerosol Transport Simulation over West Africa: Effects of Biomass Burning on Smoke Aerosol Distribution

AbstractSeries of aerosol transport hindcasts for West Africa were conducted using the Weather Research and Forecasting (WRF) Model coupled to chemistry within the NASA-Unified WRF (NU-WRF) framework. The transport of biomass-burning aerosols in April and December 2009 was investigated over two types of simulation domains. One-month simulations with 9-km grid spacing for April or December 2009 covered most of North and West Africa and were evaluated by comparison with measurements of the total-column aerosol optical depth, Ångström exponent, and horizontal wind components at various pressure levels. The horizontal wind components at 700 hPa were identified as key factors in determining the transport patterns of biomass-burning aerosols from sub-Saharan West Africa to the Sahel. The vertical accumulation of biomass-burning aerosols close to 700 hPa was demonstrated in 1-day simulations with 1-km horizontal grid spacing. A new simple parameterization for the effects of heat release by biomass burning was designed for this resolution and tested together with the conventional parameterization based on fixed smoke injection heights. The aerosol vertical profiles were somewhat sensitive to the selection of parameterization, except for cases with the assumption of excessive heating by biomass burning. The new parameterization works reasonably well and offers flexibility to relate smoke transport to biomass-burning plume rise that can be correlated with the satellite fire radiative power measurements, which is advantageous relative to the conventional parameterization.

Sensitivity of the WRF-Chem (V3.6.1) model to different dust emission parametrisation: assessment in the broader Mediterranean region

Abstract. In this study we aim to assess the WRF-Chem model capacity to reproduce dust transport over the eastern Mediterranean. For this reason, we compare the model aerosol optical depth (AOD) outputs to observations, focusing on three key regions: North Africa, the Arabian Peninsula and the eastern Mediterranean. Three sets of four simulations have been performed for the 6-month period of spring and summer 2011. Each simulation set uses a different dust emission parametrisation and for each parametrisation, the dust emissions are multiplied with various coefficients in order to tune the model performance. Our assessment approach is performed across different spatial and temporal scales using AOD observations from satellites and ground-based stations, as well as from airborne measurements of aerosol extinction coefficients over the Sahara. Assessment over the entire domain and simulation period shows that the model presents temporal and spatial variability similar to observed AODs, regardless of the applied dust emission parametrisation. On the other hand, when focusing on specific regions, the model skill varies significantly. Tuning the model performance by applying a coefficient to dust emissions may reduce the model AOD bias over a region, but may increase it in other regions. In particular, the model was shown to realistically reproduce the major dust transport events over the eastern Mediterranean, but failed to capture the regional background AOD. Further comparison of the model simulations to airborne measurements of vertical profiles of extinction coefficients over North Africa suggests that the model realistically reproduces the total atmospheric column AOD. Finally, we discuss the model results in two sensitivity tests, where we included finer dust particles (less than 1 µm) and changed accordingly the dust bins' mass fraction.

Estimating ground-level PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; in eastern China using aerosol optical depth determined from the GOCI satellite instrument

Abstract. We determine and interpret fine particulate matter (PM2.5) concentrations in eastern China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean geostationary ocean color imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5 / AOD ratio exhibits high consistency with ground-based measurements in Taiwan (MFB = −0.52 %) and Beijing (MFB = −8.0 %). We evaluate the satellite-derived PM2.5 versus the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in situ observations in both annual averages (r2 = 0.66, N = 494) and monthly averages (relative RMSE = 18.3 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical composition of GOCI-derived PM2.5 reveals that secondary inorganics (SO42-, NO3-, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating increase the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg m−3, with 400 million residents in regions that exceed the Interim Target-1 of the World Health Organization.

Impact of data quality and surface-to-column representativeness on the PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; / satellite AOD relationship for the contiguous United States

Abstract. Satellite-derived aerosol optical depth (AOD) observations have been used to estimate particulate matter smaller than 2.5 μm (PM2.5). However, such a relationship could be affected by the representativeness of satellite-derived AOD to surface aerosol particle mass concentration and satellite AOD data quality. Using purely measurement-based methods, we have explored the impacts of data quality and representativeness on the AOD-inferred PM2.5 / AOD relationship for the contiguous United States (CONUS). This is done through temporally and spatially collocated data sets of PM2.5 and AOD retrievals from Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). These analyses show that improving data quality of satellite AOD, such as done with data assimilation-grade retrievals, increases their correlation with PM2.5. However, overall correlation is relatively low across the CONUS. Also, integrated extinction observed within 500 m above ground level (a.g.l.), as measured by CALIOP, is not well representative of the total column AOD. Surface aerosol in the eastern CONUS is better correlated with total column AOD than in the western CONUS. The best correlation values are found for estimated dry mass CALIOP extinction at 200–300 m a.g.l. and PM2.5, but additional work is needed to address the ability of using actively sensed AOD as a proxy for PM2.5 concentrations.

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

Abstract. Long-term data sets of all-sky and clear-sky downwelling shortwave (SW) radiation, cloud cover fraction, and aerosol optical depth (AOD) were analyzed together with surface concentrations from several networks (e.g., Surface Radiation Budget Network (SURFRAD), Clean Air Status and Trend Network (CASTNET), Interagency Monitoring of Protection Visual Environments (IMPROVE) and Atmospheric Radiation Measurement (ARM)) in the United States (US). Seven states with varying climatology were selected to better understand the effects of aerosols and clouds on SW radiation. This analysis aims to assess the effects of reductions in anthropogenic aerosol burden resulting from substantial reductions in emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) over the past 16 yr across the US, based on trends in SW radiation. The SO2 and NOx emission data show decreasing trends from 1995 to 2010, which indirectly validates the effects of the Clean Air Act (CAA) in the US. Meanwhile, the total column AOD and surface total PM2.5 observations also show decreasing trends in the eastern US but slightly increasing trends in the western US. Moreover, measured surface concentrations of several other pollutants (i.e., SO2, SO4 and NOx) have similar behavior to AOD and total PM2.5. Analysis of the observed data shows strong increasing trends in all-sky downwelling SW radiation with decreasing trends in cloud cover. However, since observations of both all-sky direct and diffuse SW radiation show increasing trends, there may be other factors contributing to the radiation trends in addition to the decreasing trends in overall cloud cover. To investigate the role of direct radiative effects of aerosols, clear-sky downwelling radiation is analyzed so that cloud effects are eliminated. However, similar increasing trends in clear-sky total and diffuse SW radiation are observed. While significantly decreasing trends in AOD and surface PM2.5 concentrations along with increasing SW radiation (both all-sky and clear-sky) in the eastern US during 1995–2010 imply the occurrence of direct aerosol mediated "brightening", the increasing trends of both all-sky and clear-sky diffuse SW radiation contradicts this conclusion since diffuse radiation would be expected to decrease as aerosols direct effects decrease and cloud cover decreases. After investigating several confounding factors, the increasing trend in clear-sky diffuse SW may be due to more high-level cirrus from increasing air traffic over the US. The clear-sky radiation observations in the western US also show indications of "brightening" even though the AOD, PM2.5 and surface concentration do not vary drastically. This outcome was not unexpected because the CAA controls were mainly aimed at reducing air pollutant emissions in the eastern US and air pollutant levels in the western US were much lower at the onset. This suggests other factors affect the "brightening" especially in the western US.

Comparison of GEOS‐Chem aerosol optical depth with AERONET and MISR data over the contiguous United States

Aerosol optical properties simulated by the global 3‐D tropospheric chemistry and transport model Goddard Earth Observing System (GEOS)‐Chem (GC) from 2008 to 2010 over the contiguous United States were evaluated with ground observations from Aerosol Robotic Network (AERONET) sites and aerosol products reported by the Multiangle Imaging Spectroradiometer (MISR). Overall, the correlation coefficient (r) and regression slope between AERONET and GC2° × 2.5° (2° latitude × 2.5° longitude) daily total column aerosol optical depth (AOD) were 0.6 and 0.51, respectively. After using the nested GC0.5° × 0.667° model to control for spatial variability, removing several outliers, and averaging over a monthly timescale, the agreement was significantly improved to an r of 0.84 and a slope of 0.75. Seasonal, hourly, and geographical statistics for GC0.5° × 0.667° and AERONET AODs show a similar data range and variation, with higher mean values in the summer, the evening, and in the eastern U.S. Smaller correlation coefficients are seen in the summer and winter, in the evening, and in the western U.S. To investigate the optical properties of major GC tracers, MISR level 2 aerosol products were used to calculate inorganic aerosol, dust, and absorbing non‐dust AOD. Both GC and MISR suggest that on average, inorganic aerosol has the highest AOD (GC: 0.071, MISR: 0.089) nationally, followed by absorbing non‐dust species (GC: 0.025, MISR: 0.041), and dust (GC: 0.013, MISR: 0.014). The large discrepancies in our intercomparison are due to GC underestimation of inorganic aerosol levels during all four seasons in the western U.S. and dust during summer in the eastern U.S., along with overestimation of summertime‐absorbing non‐dust species over the northwestern U.S. These uncertainties are attributed to underestimation of inorganic aerosol emissions in more polluted western regions, the transport of Sahara dust in the summer, misuse of the fire files, MISR retrieval uncertainties in the surface, and choice of aerosol models.

Aerosol retrieval experiments in the ESA Aerosol_cci project

Abstract. Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust).

Optimal estimation for global ground‐level fine particulate matter concentrations

We develop an optimal estimation (OE) algorithm based on top‐of‐atmosphere reflectances observed by the MODIS satellite instrument to retrieve near‐surface fine particulate matter (PM2.5). The GEOS‐Chem chemical transport model is used to provide prior information for the Aerosol Optical Depth (AOD) retrieval and to relate total column AOD to PM2.5. We adjust the shape of the GEOS‐Chem relative vertical extinction profiles by comparison with lidar retrievals from the CALIOP satellite instrument. Surface reflectance relationships used in the OE algorithm are indexed by land type. Error quantities needed for this OE algorithm are inferred by comparison with AOD observations taken by a worldwide network of sun photometers (AERONET) and extended globally based upon aerosol speciation and cross correlation for simulated values, and upon land type for observational values. Significant agreement in PM2.5 is found over North America for 2005 (slope = 0.89; r = 0.82; 1‐σ error = 1 µg/m3 + 27%), with improved coverage and correlation relative to previous work for the same region and time period, although certain subregions, such as the San Joaquin Valley of California are better represented by previous estimates. Independently derived error estimates of the OE PM2.5 values at in situ locations over North America (of ±(2.5 µg/m3 + 31%) and Europe of ±(3.5 µg/m3 + 30%) are corroborated by comparison with in situ observations, although globally (error estimates of ±(3.0 µg/m3 + 35%), may be underestimated. Global population‐weighted PM2.5 at 50% relative humidity is estimated as 27.8 µg/m3 at 0.1° × 0.1° resolution.

Fifteen‐year aerosol optical depth climatology for Salt Lake City

Aerosol optical depth (AOD) and its wavelength dependence have been measured for the past 15 years in the Salt Lake City metropolitan area using a multifilter rotating shadowband radiometer. The instrument has not experienced a major hardware failure. It has been continuously field calibrated for extraterrestrial responses in its five aerosol channels. The instrument's cosine response was measured in 1996 and again in 2012. In our analysis of this 15 year data set, linear interpolation of these two cosine responses was used to approximate the angular response between the two characterizations. The Salt Lake City aerosol burden increased through the mid‐2000s, but has dropped to its lowest level of the record since that time despite a population increase of approximately 25%. Annually, the aerosol burden is highest in midspring and midsummer with relatively coarse aerosols during the spring peak and fine aerosols during the summer peak. There is no indication of a diurnal cycle in AOD. There is a significant, but low, correlation between PM2.5 and 500 nm AOD, and a slightly lower correlation between PM10 and 500 nm AOD. The correlations between the surface‐based measurements and total column AOD explain only 13% and 9% of the variance, respectively. Measurements are continuing to track future trends.

Aerosol, Ozone and Water Vapour Distributions Observed over Land and Sea Regions during INDOEX Field Phases

Extensive land- and ocean-based experiments involving active and passive remote sensing of aerosols and minor constituents have been conducted simultaneously over Pune and over the Indian Ocean and Arabian Sea during the INDian Ocean EXperiment (INDOEX) field phases with an aim to study the interface between the polluted continental air-mass and pristine marine air-mass, and the underlying circulat ion and Inter Tropical Convergence Zone (ITCZ) phenomena, which mixes the polluted air mass from Northern hemisphere with the pristine air mass from the Southern hemisphere. In this communicat ion, we report some important findings of the special observational programs which were carried out during the First Field Phase (FFP) i.e. fro m 17 February to 31 March 1998 and Intense Field Phase (IFP) i.e. fro m 1 January to 31 March 1999 of the INDOEX. These programs involve synchronous measurements of aerosol, ozone and precipitable water vapor using ground-based lidar, sunphotometer / spectroradiometer and ozone / water vapor monitor at the Indian Institute of Tropical Meteorology (IITM ), Pune, India, and aerosol characterization over the Indian Ocean and Arabian Sea utilizing a mult i-channel solar radio meter installed onboard Ocean Research Vessel (ORV) Sagar Kanya ship. Besides significant deviations between aerosol features over the land and oceanic regions, the lidar derived aerosol colu mn content (ACC) in the boundary layer, and radio meter derived height-integrated aerosol optical depth (AOD) show significant trend and characteristic changes in aerosol size distribution over land during both FFP and IFP. Moreover, the IFP measurements indicate higher aerosol ext inction (particularly in the initial period) as co mpared to those of FFP. On some experimental days, the land AODs appear to be of the magnitude similar to those of marine AODs observed close to the Indian subcontinent and adjoining South Asian regions. The variations in AOD over land also show an association with those observed over ocean, particularly near the coast. Besides an increasing trend in total colu mn ozone throughout the IFP, it exhib its a specific relat ionship with those observed in AOD and water vapor over land. Co mparison between the boundary layer and total column AODs reveals that the observed increasing trend in AOD is not confined to the boundary layer alone but extends to higher altitudes with significant contribution fro m the former to the latter.

Enhancement of OMI aerosol optical depth data assimilation using artificial neural network

A regional chemical transport model assimilated with daily mean satellite and ground-based aerosol optical depth (AOD) observations is used to produce three-dimensional distributions of aerosols throughout Europe for the year 2005. In this paper, the AOD measurements of the Ozone Monitoring Instrument (OMI) are assimilated with Polyphemus model. In order to overcome missing satellite data, a methodology for preprocessing AOD based on neural network (NN) is proposed. The aerosol forecasts involve two-phase process assimilation and then a feedback correction process. During the assimilation phase, the total column AOD is estimated from the model aerosol fields. The main contribution is to adjust model state to improve the agreement between the simulated AOD and satellite retrievals of AOD. The results show that the assimilation of AOD observations significantly improves the forecast for total mass. The errors on aerosol chemical composition are reduced and are sometimes vanished by the assimilation procedure and NN preprocessing, which shows a big contribution to the assimilation process.

Polar aerosol characterization, sources and impacts

Aerosols are known to cause important effects on weather and climate of Polar Regions and their radiation balance of the polar surface-atmosphere system, especially in the regions characterized by high surface-reflectance conditions, which also prevails the heterogeneous chemistry of aerosols. Therefore, the knowledge of the aerosol physical and optical properties needs to be improved on both spatial and temporal scales. To characterize these physico-chemical and optical properties, studies have been carried out over both the polar regions [Antarctica (‘Maitri’ (70.76oS, 11.74oE) and Arctic “Himadri” (79°N, 11°E) during the summer period of 24th (2004-05), 26th (2006-07) Indian Antarctica Expedition, and during 14th Indian Arctic Expedition in 2010. Total column aerosol optical depth (AOD), ozone (TCO), precipitable water content (PWC), and direct radiative forcing using a multi-channel solar-radiometer (Microtops II); and short-wave global radiative flux using a wide-band pyranometer for their characteristics. In the Arctic, an Andersen Sampler, Black Carbon Aethalometer was also operated to determine the chemical properties of aerosols.&#x0D; The aerosol optical, physical and radiative properties, and their interface with simultaneously measured gases and their chemical composition have been investigated. The results showed that the daily mean AOD at a characteristic wavelength of 500 nm was found to be 0.042 with an average Angstrom coefficient of 0.24, revealing abundance of coarse-mode particles in Antarctica, and Arctic average AOD was observed 0.11 with an average Angstrom coefficient of 2.84, suggesting fine-mode particles. The TCO measured by the surface-based ozone monitor matched reasonably within 5% with that of the Total Ozone Mapping Spectrometer (TOMS) satellite sensor. Variability in ozone on daily scale, during the study period, was less than 4% over the Antarctica region and more or less same for Arctic.&#x0D; The January 2005 fluxes were found to be less by about 20% as compared to those in February 2005. The average short-wave direct radiative forcing due to aerosols showed cooling at the surface with an average value of -0.47 W/m2 during the study period. In this paper, we briefly describe the equipment deployed, data archival, their analysis techniques and salient results obtained over the Indian polar stations, ‘Maitri’ and ‘Himadri’.