Sun Photometer Aerosol Optical Depth Research Articles

Variation of Aerosol Optical Depth Measured by Sun Photometer at a Rural Site near Beijing during the 2017–2019 Period

In recent years, the Beijing–Tianjin–Hebei region has become one of the worst areas for haze pollution in China. Sun photometers are widely used for aerosol optical property monitoring due to the advantages of fully automatic acquisition, simple maintenance, standardization of data processing, and low uncertainty. Research sites are mostly concentrated in cities, while the long-term analysis of aerosol optical depth (AOD) for the pollution transmission channel in rural Beijing is still lacking. Here, we obtained an AOD monitoring dataset from August 2017 to March 2019 using the ground-based CE-318 sun photometer at the Gucheng meteorological observation site in southwest Beijing. These sun photometer AOD data were used for the ground-based validation of MODIS (Moderate Resolution Imaging Spectroradiometer) and AHI (Advanced Himawari Imager) AOD data. It was found that MODIS and AHI can reflect AOD variation trends by sun photometer on daily, monthly, and seasonal scales. The original AOD measurements of the sun photometer show good correlations with satellite observations by MODIS (R = 0.97), and AHI (R = 0.89), respectively, corresponding to their different optimal spatial and temporal windows for matching with collocated satellite ground pixels. However, MODIS is less stable for aerosols of different concentrations and particle sizes. Most of the linear regression intercepts between the satellite and the photometer are less than 0.1, indicating that the errors due to surface reflectance in the inversion are small, and the slope is least biased (AHI: slope = 0.91, MODIS: slope = 0.18) in the noon period (11 a.m.–2 p.m.) and most biased in summer (AHI: slope = 0.77, MODIS: slope = 1.31), probably due to errors in the aerosol model. The daily and seasonal variation trends between CE-318 AOD measurements in the Gucheng site and fine particulate observations from the national air quality site nearby were also compared and investigated. In addition, a typical haze–dust complex pollution event in North China was analyzed and the changes in AOD during the pollution event were quantified. In processing, we use sun photometer and satellite AOD data in combination with meteorological and PM data. Overall, this paper has implications for the study of AOD evolution patterns at different time scales, the association between PM2.5 concentrations and AOD changes, and pollution monitoring.

PM<sub>2.5</sub> surface concentrations in southern West African urban areas based on sun photometer and satellite observations

Abstract. Southern West Africa (SWA) is influenced by large numbers of aerosol particles of both anthropogenic and natural origins. Anthropogenic aerosol emissions are expected to increase in the future due to the economical growth of African megacities. In this paper, we investigate the aerosol optical depth (AOD) in the coastal area of the Gulf of Guinea using sun photometer and MODIS satellite observations. A network of lightweight handheld sun photometers have been deployed in SWA from December 2014 to April 2017 at five different locations in Côte d'Ivoire and Benin. The handheld sun photometer measures the solar irradiance at 465, 540 and 619 nm and is operated manually once per day. Handheld-sun-photometer observations are complemented by available AERONET sun photometer observations and MODIS level 3 time series between 2003 and 2019. MODIS daily level 3 AOD agrees well with sun photometer observations in Abidjan and Cotonou (correlation coefficient R=0.89 and RMSE = 0.19). A classification based on the sun photometer AOD and Ångström exponent (AE) is used to separate the influence of coarse mineral dust and urban-like aerosols. The AOD seasonal pattern is similar for all the sites and is clearly influenced by the mineral dust advection from December to May. Sun photometer AODs are analyzed in coincidence with surface PM2.5 concentrations to infer trends in the particulate pollution levels over conurbations of Abidjan (Côte d'Ivoire) and Cotonou (Benin). PM2.5-to-AOD conversion factors are evaluated as a function of the season and the aerosol type identified in the AE classification. The highest PM2.5 concentrations (up to 300 µg m−3) are associated with the advection of mineral dust in the heart of the dry season (December–February). Annual means are around 30 µg m−3, and 80 % of days in the winter dry season have a value above 35 µg m−3, while concentrations remain below 16 µg m−3 from May to September. No obvious trend is observed in the 2003–2019 MODIS-derived PM2.5 time series. However the short dry period (August–September), when urban-like aerosols dominate, is associated with a monotonic trend between 0.04 and 0.43 µgm-3yr-1 in the PM2.5 concentrations over the period 2003–2017. The monotonic trend remains uncertain but is coherent with the expected increase in combustion aerosol emissions in SWA.

Spatiotemporal variability of optical properties of aerosols over the Indo-Gangetic Plain during 2011–2015

The present study reports daily, monthly, and seasonal variations of aerosol optical depth (AOD) using aerosol robotic network (AERONET), MICROTOPS-II Sunphotometer, and Moderate Resolution Imaging Spectroradiometer (MODIS) data over three most polluted cities such as Kanpur, Varanasi, and Jaipur in the Indo-Gangetic Plain during 2011–2015. The monthly mean variations of AOD and Angstrom Exponent were also presented and compared with the meteorological parameters for all three cities. The concentrations of AODs in Kanpur and Varanasi were observed higher than in Jaipur throughout the study period. Overall maximum correlation (R2 = 0.74) was found in between AERONET and MODIS AOD in the winter season over Kanpur during 2011–2015, whereas the lowest correlation (R2 = 0.41) was found in between MICROTOPS-II Sunphotometer and MODIS AOD over Varanasi for the same period in the pre-monsoon season. Spectral variations of AODs at five different wavelengths, i.e., 380, 440, 500, 675, and 870 nm, were derived using AERONET for Jaipur and Kanpur and using MICROTOPS-II Sunphotometer for Varanasi during 2011–2015 inferred clearly that increasing wavelength provides decreasing AODs. The Hybrid Single-Particle Lagrangian Integrated Trajectories model was used for the backward trajectories analysis to assess the sources of large aerosol loadings over Jaipur, Kanpur, and Varanasi cities during some typical days.

A Multi Linear Regression Model to Derive Dust PM10 in the Sahel Using AERONET Aerosol Optical Depth and CALIOP Aerosol Layer Products

Due to a limited number of monitoring stations in Western Africa, the impact of mineral dust on PM10 surface concentrations is still poorly known. We propose a new method to retrieve PM10 dust surface concentrations from sun photometer aerosol optical depth (AOD) and CALIPSO/CALIOP Level 2 aerosol layer products. The method is based on a multi linear regression model that is trained using co-located PM10, AERONET and CALIOP observations at 3 different locations in the Sahel. In addition to the sun photometer AOD, the regression model uses the CALIOP-derived base and top altitude of the lowermost dust layer, its AOD, the columnar total and columnar dust AOD. Due to the low revisit period of the CALIPSO satellite, the monthly mean annual cycles of the parameters are used as predictor variables rather than instantaneous observations. The regression model improves the correlation coefficient between monthly mean PM10 and AOD from 0.15 (AERONET AOD only) to 0.75 (AERONET AOD and CALIOP parameters). The respective high and low PM10 concentration during the winter dry season and summer season are well produced. Days with surface PM10 above 100 μg/m3 are better identified when using the CALIOP parameters in the multi linear regression model. The number of true positives (actual and predicted concentrations above the threshold) is increased and leads to an improvement in the classification sensitivity (recall) by a factor 1.8. Our methodology can be extrapolated to the whole Sahel area provided that satellite derived AOD maps are used in order to create a new dataset on population exposure to dust events in this area.

A multi-axis differential optical absorption spectroscopy aerosol profile retrieval algorithm for high-altitude measurements: application to measurements at Schneefernerhaus (UFS), Germany

Abstract. We present a new aerosol extinction profile retrieval algorithm for multi-axis differential optical absorption spectrometer (MAX-DOAS) measurements at high-altitude sites. The algorithm is based on the lookup table method. It is applied to retrieve aerosol extinction profiles from the long-term MAX-DOAS measurements (February 2012 to February 2016) at the Environmental Research Station Schneefernerhaus (UFS), Germany (47.417∘ N, 10.980∘ E), which is located near the summit of Zugspitze at an altitude of 2650 m. The lookup table consists of simulated O4 differential slant column densities (DSCDs) corresponding to numerous possible aerosol extinction profiles. The sensitivities of O4 absorption to several parameters were investigated for the design and parameterization of the lookup table. In the retrieval, simulated O4 DSCDs for each possible profile are derived by interpolating the lookup table to the observation geometries. The cost functions are calculated for each aerosol profile in the lookup table based on the simulated O4 DSCDs, the O4 DSCD observations, and the measurement uncertainties. Valid profiles are selected from all the possible profiles according to the cost function, and the optimal solution is defined as the weighted mean of all the valid profiles. A comprehensive error analysis is performed to better estimate the total uncertainty. Based on the assumption that the lookup table covers all possible profiles under clear-sky conditions, we determined a set of O4 DSCD scaling factors for different elevation angles and wavelengths. The profiles retrieved from synthetic measurement data can reproduce the synthetic profile. The results also show that the retrieval is insensitive to measurement noise, indicating the retrieval is robust and stable. The aerosol optical depths (AODs) retrieved from the long-term measurements were compared to coinciding and co-located sun photometer observations. High correlation coefficients (R) of 0.733 and 0.798 are found for measurements at 360 and 477 nm, respectively. However, especially in summer, the sun photometer AODs are systematically higher than the MAX-DOAS retrievals by a factor of ∼2. The discrepancy might be related to the limited measurement range of the MAX-DOAS and is probably also related to the decreased sensitivity of the MAX-DOAS measurements at higher altitudes. The MAX-DOAS measurements indicate the aerosol extinction decreases with increasing altitude during all seasons, which agrees with the co-located ceilometer measurements. Our results also show maximum AOD and maximum Ångström exponent in summer, which is consistent with observations at an AERONET station located ∼43 km from the UFS.

The potential of elastic and polarization lidars to retrieve extinction profiles

Abstract. A new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem.

Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012

Abstract. Satellites provide information on the temporal and spatial distributions of aerosols on regional and global scales. With the same method applied to a single sensor all over the world, a consistent data set is to be expected. However, the application of different retrieval algorithms to the same sensor and the use of a series of different sensors may lead to substantial differences, and no single sensor or algorithm is better than any other everywhere and at all times. For the production of long-term climate data records, the use of multiple sensors cannot be avoided. The Along Track Scanning Radiometer (ATSR-2) and the Advanced ATSR (AATSR) aerosol optical depth (AOD) data sets have been used to provide a global AOD data record over land and ocean of 17 years (1995–2012), which is planned to be extended with AOD retrieved from a similar sensor. To investigate the possibility of extending the ATSR data record to earlier years, the use of an AOD data set from the Advanced Very High Resolution Radiometer (AVHRR) is investigated. AOD data sets used in this study were retrieved from the ATSR sensors using the ATSR Dual View algorithm ADV version 2.31, developed by Finnish Meteorological Institute (FMI), and from the AVHRR sensors using the aerosol optical depth over land (ADL) algorithm developed by RADI/CAS. Together, these data sets cover a multi-decadal period (1987–2012). The study area includes two contrasting areas, both in regards to aerosol content and composition and surface properties, i.e. a region over north-eastern China, encompassing a highly populated urban/industrialized area (Beijing–Tianjin–Hebei) and a sparsely populated mountainous area. Ground-based AOD observations available from ground-based sun photometer AOD data in AERONET and CARSNET are used as a reference, together with broadband extinction method (BEM) data at Beijing to cover the time before sun photometer observations became available in the early 2000s. In addition, MODIS-Terra C6.1 AOD data are used as a reference data set over the wide area where no ground-based data are available. All satellite data over the study area were validated against the reference data, showing the qualification of MODIS for comparison with ATSR and AVHRR. The comparison with MODIS shows that AVHRR performs better than ATSR in the north of the study area (40∘ N), whereas further south ATSR provides better results. The validation against sun photometer AOD shows that both AVHRR and ATSR underestimate the AOD, with ATSR failing to provide reliable results in the wintertime. This is likely due to the highly reflecting surface in the dry season, when AVHRR-retrieved AOD traces both MODIS and reference AOD data well. However, AVHRR does not provide AOD larger than about 0.6 and hence is not reliable when high AOD values have been observed over the last decade. In these cases, ATSR performs much better for AOD up to about 1.3. AVHRR-retrieved AOD compares favourably with BEM AOD, except for AOD higher than about 0.6. These comparisons lead to the conclusion that AVHRR and ATSR AOD data records each have their strengths and weaknesses that need to be accounted for when combining them in a single multi-decadal climate data record.

Evaluation of the Aqua-MODIS C6 and C6.1 Aerosol Optical Depth Products in the Yellow River Basin, China

In this study, Aqua-Moderate Resolution Imaging Spectroradiometer (MODIS) Collection (C6) and C6.1 Dark Target aerosol optical depth (AOD) retrievals at 3 km (DT3K) and 10 km (DT10K), Deep Blue AOD retrievals at 10 km (DB10K), and combined DT and DB (DTB) AOD retrievals at 10 km resolutions were validated from 2002 to 2014 against ground-based sunphotometer AOD measurements obtained from the Chinese aerosol remote sensing network (CARSNET). The CARSNET AOD data were obtained for sites at Mt. Waliguan (MW), Lanzhou (LZ), Ulate (UL), and Zhengzhou (ZZ) located in the Yellow River basin (YERB) region, China. Errors and agreement between satellite and ground data were reported using Pearson’s correlation (R) and relative mean bias (RMB). Results showed that the DT3K C6.1 highest quality flag (QF = 3) AOD retrievals were well correlated with the sunphotometer AOD data, with an R of 0.82 and an RMB of 1.01. Overestimation and underestimation in DT AOD retrievals were observed for AOD > 1.1 and AOD < 1.1, respectively. A significant underestimation of 37% in DB10K AOD retrievals was observed across all the sites except ZZ, which was indicated by a low-value RMB (0.63). Spatial distribution maps showed high AOD values (>0.8) over the lower part of the YERB and low AOD values (<0.4) across the upstream part of the YERB. This might be due to a large number of aerosol emissions over the lower developed areas and a scarcity of aerosols over the upstream mountain areas. Overall, this study supports the use of DT10K C6.1 AOD retrievals over the western semi-arid and arid regions of the YERB and DTB10K AOD retrievals over the north-central water system and eastern plain regions of the YERB.

Aerosol monitoring in Siberia using an 808 nm automatic compact lidar

Abstract. Our study provides new information on aerosol-type seasonal variability and sources in Siberia using observations (ground-based lidar and sun photometer combined with satellite measurements). A micropulse lidar emitting at 808 nm provided almost continuous aerosol backscatter measurements for 18 months (April 2015 to September 2016) in Siberia, near the city of Tomsk (56∘ N, 85∘ E). A total of 540 vertical profiles (300 daytime and 240 night-time) of backscatter ratio and aerosol extinction have been retrieved over periods of 30 min, after a careful calibration factor analysis. Lidar ratio and extinction profiles are constrained with sun-photometer aerosol optical depth at 808 nm (AOD808) for 70 % of the daytime lidar measurements, while 26 % of the night-time lidar ratio and AOD808 greater than 0.04 are constrained by direct lidar measurements at an altitude greater than 7.5 km and where a low aerosol concentration is found. An aerosol source apportionment using the Lagrangian FLEXPART model is used in order to determine the lidar ratio of the remaining 48 % of the lidar database. Backscatter ratio vertical profile, aerosol type and AOD808 derived from micropulse lidar data are compared with sun-photometer AOD808 and satellite observations (CALIOP space-borne lidar backscatter and extinction profiles, Moderate Resolution Imaging Spectroradiometer (MODIS) AOD550 and Infrared Atmospheric Sounding Interferometer (IASI) CO column) for three case studies corresponding to the main aerosol sources with AOD808>0.2 in Siberia. Aerosol typing using the FLEXPART model is consistent with the detailed analysis of the three case studies. According to the analysis of aerosol sources, the occurrence of layers linked to natural emissions (vegetation, forest fires and dust) is high (56 %), but anthropogenic emissions still contribute to 44 % of the detected layers (one-third from flaring and two-thirds from urban emissions). The frequency of dust events is very low (5 %). When only looking at AOD808>0.1, contributions from taiga emissions, forest fires and urban pollution become equivalent (25 %), while those from flaring and dust are lower (10 %–13 %). The lidar data can also be used to assess the contribution of different altitude ranges to the large AOD. For example, aerosols related to the urban and flaring emissions remain confined below 2.5 km, while aerosols from dust events are mainly observed above 2.5 km. Aerosols from forest fire emissions are observed to be the opposite, both within and above the planetary boundary layer (PBL).

A Simple and Universal Aerosol Retrieval Algorithm for Landsat Series Images Over Complex Surfaces

AbstractOperational aerosol optical depth (AOD) products are available at coarse spatial resolutions from several to tens of kilometers. These resolutions limit the application of these products for monitoring atmospheric pollutants at the city level. Therefore, a simple, universal, and high‐resolution (30 m) Landsat aerosol retrieval algorithm over complex urban surfaces is developed. The surface reflectance is estimated from a combination of top of atmosphere reflectance at short‐wave infrared (2.22 μm) and Landsat 4–7 surface reflectance climate data records over densely vegetated areas and bright areas. The aerosol type is determined using the historical aerosol optical properties derived from the local urban Aerosol Robotic Network (AERONET) site (Beijing). AERONET ground‐based sun photometer AOD measurements from five sites located in urban and rural areas are obtained to validate the AOD retrievals. Terra MODerate resolution Imaging Spectrometer Collection (C) 6 AOD products (MOD04) including the dark target (DT), the deep blue (DB), and the combined DT and DB (DT&DB) retrievals at 10 km spatial resolution are obtained for comparison purposes. Validation results show that the Landsat AOD retrievals at a 30 m resolution are well correlated with the AERONET AOD measurements (R2 = 0.932) and that approximately 77.46% of the retrievals fall within the expected error with a low mean absolute error of 0.090 and a root‐mean‐square error of 0.126. Comparison results show that Landsat AOD retrievals are overall better and less biased than MOD04 AOD products, indicating that the new algorithm is robust and performs well in AOD retrieval over complex surfaces. The new algorithm can provide continuous and detailed spatial distributions of AOD during both low and high aerosol loadings.

BIOMASS BURNING RELATED POLLUTIONS AND THEIR CONTRIBUTIONS TO THE LOCAL AIR QUALITY IN HONG KONG

Abstract. In this study, we present a quantitative estimation of the impacts of biomass burning emissions from different source regions to the local air quality in Hong Kong in 2014 using global chemistry transport model simulations, sun photometer measurements, satellite observations and local monitoring network data. This study focuses on two major biomass burning pollutants, black carbon aerosols and carbon monoxide (CO). The model simulations of atmospheric black carbon and CO show excellent agreement with sun photometer aerosol optical depth (AOD) measurements, satellite CO columns observations and local monitoring stations data. From the model simulation results, we estimated that biomass burning contributes 12 % of total black carbon and 16 % of atmospheric CO in Hong Kong on annual average. South East Asia shows the largest influence to the black carbon and CO levels in Hong Kong, accounts for 11 % of the total atmospheric black carbon and 8 % of CO. Biomass burning in North East Asia and Africa also show significant impacts to Hong Kong. Elevated levels of atmospheric black carbon aerosols and CO were observed during springtime (March and April) which is mainly due to the enhancement of biomass burning contributions. Black carbon and CO originating from biomass burning sources are estimated to contribute 40 % of atmospheric black carbon and 28 % of CO in Hong Kong during March 2014. An investigation focusing on the biomass burning pollution episode during springtime suggests the intensified biomass burning activities in the Indochinese Peninsula are the major sources of black carbon and CO in Hong Kong during the time.

Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan

Visible Infrared Imaging Radiometer Suite (VIIRS) is a next-generation polar-orbiting operational environmental sensor with a capability for global aerosol observations. A comprehensive validation of VIIRS products is significant for improving product quality, assessing environment quality for human life, and studying regional climate change. In this study, three-year (from 1 January 2014 to 31 December 2016) records of VIIRS Intermediate Product (IP) data and Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals on aerosol optical depth (AOD) at 550 nm were evaluated by comparing them to ground sun photometer measurements over Wuhan. Results indicated that VIIRS IP retrievals were underestimated by 5% for the city. A comparison of VIIRS IP retrievals and ground sun photometer measurements showed a lower R2 of 0.55 (0.79 for Terra-MODIS and 0.76 for Aqua-MODIS), with only 52% of retrievals falling within the expected error range established by MODIS over land (i.e., ±(0.05 + 0.15AOD)). Bias analyses with different Ångström exponents (AE) demonstrated that land aerosol model selection of the VIIRS retrieval over Wuhan was appropriate. However, the larger standard deviations (i.e., uncertainty) of VIIRS AODs than MODIS AODs could be attributed to the less robust retrieval algorithm. Monthly variations displayed largely underestimated AODs of VIIRS in winter, which could be caused by a large positive bias in surface reflectance estimation due to the sparse vegetation and greater surface brightness of Wuhan in this season. The spatial distribution of VIIRS and MODIS AOD observations revealed that the VIIRS IP AODs over high-pollution areas (AOD > 0.8) with sparse vegetation were underestimated by more than 20% in Wuhan, and 40% in several regions. Analysis of several clear rural areas (AOD < 0.2) with native vegetation indicated an overestimation of about 20% in the northeastern region of the city. These findings showed that the VIIRS IP AOD at 550 nm can provide a solid dataset with a high resolution (750 m) for quantitative scientific investigations and environmental monitoring over Wuhan. However, the performance of dark target algorithms in VIIRS was associated with aerosol types and ground vegetation conditions.

Biomass burning sources and their contributions to the local air quality in Hong Kong

In this paper, we present a quantitative estimation of the impacts of biomass burning emissions from different source regions to the local air quality in Hong Kong in 2014 using global chemistry transport model simulations, sun photometer measurements, satellite observations and local monitoring network data. This study focuses on two major biomass burning pollutants, black carbon aerosols and carbon monoxide (CO). The model simulations of atmospheric black carbon and CO show excellent agreement with sun photometer aerosol optical depth (AOD) measurements, satellite CO columns observations and local monitoring stations data. From the model simulation results, we estimated that biomass burning contributes 12% of total black carbon and 16% of atmospheric CO in Hong Kong on annual average. South East Asia shows the largest influence to the black carbon and CO levels in Hong Kong, accounts for 11% of the total atmospheric black carbon and 8% of CO. Biomass burning in North East Asia and Africa also show significant impacts to Hong Kong. Elevated levels of atmospheric black carbon aerosols and CO were observed during springtime (March and April) which is mainly due to the enhancement of biomass burning contributions. Black carbon and CO originating from biomass burning sources are estimated to contribute 40% of atmospheric black carbon and 28% of CO in Hong Kong during March 2014. An investigation focusing on the biomass burning pollution episode during springtime suggests the intensified biomass burning activities in the Indochinese Peninsula are the major sources of black carbon and CO in Hong Kong during the time.

Validation of MODIS and VIIRS derived aerosol optical depth over complex coastal waters

In this study, the Simplified Aerosol Retrieval Algorithm (SARA) was applied to both MODIS and Visible Infrared Imaging Radiometer Suits (VIIRS) images to retrieve aerosol optical depth (AOD) over water for blue, green and red wavelengths at 500m (MODISSARA) and 750m (VIIRSSARA) resolutions, respectively. Retrievals were compared with the Terra–MODIS Dark Target (DT) AOD at 3km resolution (MODIS3K) and the VIIRS Environmental Data Record (VIIRSEDR) AOD at 6km resolution. Validation was conducted using 86 Microtops II Sun photometer AOD measurements collected over different classes of water quality (low to high sediment levels) for seven days (6, 8, 9, 13, and 15, 16 and 17 October 2014) between 10:00 to 15:00 local time. Thirty-eight to fifty percent and 44–54% of the MODIS3K and the VIIRSEDR AOD retrievals respectively, fall within the expected error (EE) with root mean square error from 0.12 to 0.14 and mean absolute error from 0.10 to 0.11. The MODISSARA and the VIIRSSARA AOD retrievals are well correlated with the ground–based measurements (R: MODISSARA=0.86–0.89 and VIIRSSARA=0.85–0.94), with a larger number of retrievals falling within the EE MODISSARA=73–77% and VIIRSSARA=71–82%) than MODIS3K and VIIRSEDR. The results indicate that the SARA algorithm is more robust than MODIS3K and VIIRSEDR global AOD products, and can retrieve accurate AOD over low to highly sedimented water surfaces, similar to good AOD retrievals over land.

Multiyear Aerosol Study Based on Lidar&Sunphotometer Measurements in Romania

This observational study focused on three-years time-averaged data set (January 2012–2015). An investigation of long-term trends was performed on two different data sets derived from active and passive remote sensing measurements in Magurele, Romania.Measurements of sun photometer aerosol optical depth (AOD) at 500 nm and 340 nm show the mean values of 0.230 ±0 .118 and 0.398 ± 0.185, respectively. The lidar AOD at 532 and 355nm has a mean of 0.271 ±.0.164 and 0.472 ± 0.165 respectively. The highest seasonal mean value was measured by the lidar during the summer of 2014 while the lowest seasonal value was measured by the sunphotometer in February 2012.The origin of atmospheric aerosols has been analyzed using both backtajectories of Hysplit and Circulation Type Classification (CTCs) methods.

Estimation of surface-level PM concentration from satellite observation taking into account the aerosol vertical profiles and hygroscopicity

Surface-level PM10 distribution was estimated from the satellite aerosol optical depth (AOD) products, taking the account of vertical profiles and hygroscopicity of aerosols over Jeju, Korea during March 2008 and October 2009. In this study, MODIS AOD data from the Terra and Aqua satellites were corrected with aerosol extinction profiles and relative humidity data. PBLH (Planetary Boundary Layer Height) was determined from MPLNET lidar-derived aerosol extinction coefficient profiles. Through statistical analysis, better agreement in correlation (R = 0.82) between the hourly PM10 concentration and hourly average Sunphotometer AOD was the obtained when vertical fraction method (VFM) considering Haze Layer Height (HLH) and hygroscopic growth factor f(RH) was used. The validity of the derived relationship between satellite AOD and surface PM10 concentration clearly demonstrates that satellite AOD data can be utilized for remote sensing of spatial distribution of regional PM10 concentration.

Impacts of elevated-aerosol-layer and aerosol type on the correlation of AOD and particulate matter with ground-based and satellite measurements in Nanjing, southeast China

Assessment of the correlation between aerosol optical depth (AOD) and particulate matter (PM) is critical to satellite remote sensing of air quality, e.g. ground PM10 and ground PM2.5. This study evaluates the impacts of aloft-aerosol-plume and aerosol-type on the correlation of AOD–PM by using synergistic measurement of a polarization-sensitive Raman–Mie lidar, CIMEL sunphotometer (SP) and TEOM PM samplers, as well as the satellite MODIS and CALIPSO, during April to July 2011 in Nanjing city (32.05○N/118.77○E), southeast China. Aloft-aerosol-layer and aerosol types (e.g. dust and non-dust or urban aerosol) are identified with the range-resolved polarization lidar and SP measurements. The results indicate that the correlations for AOD–PM10 and AOD–PM2.5 can be much improved when screening out the aloft-aerosol-layer. The linear regression slopes show significant differences for the dust and non-dust dominant aerosols in the planetary boundary layer (PBL). In addition, we evaluate the recent released MODIS-AOD product (Collection 6) from the “dark-target” (DT) and “deep-blue” (DB) algorithms and their correlation with the PM in Nanjing urban area. The results verify that the MODIS-DT AODs show a good correlation (R=0.89) with the SP–AOD but with a systematic overestimate. In contrast, the MODIS-DB AOD shows a moderate correlation (R=0.66) with the SP–AOD but with a smaller regression intercept (0.07). Furthermore, the moderately high correlations between the MODIS–AOD and PM10 (PM2.5) are indicated, which suggests the feasibility of PM estimate using the MODIS–AOD in Nanjing city.

Dust detection from ground‐based observations in the summer global dust maximum: Results from Fennec 2011 and 2012 and implications for modeling and field observations

AbstractIn boreal summer, the central Sahara is the dustiest place on Earth. Fennec supersite 1 is located within the dust maximum. With two field seasons completed, June 2011 (intensive observation period (IOP) 1) and June 2012 (IOP2), we now have an initial measure of their representativeness. Although the number of dust event hours in IOP2 is up to 169 h (60%) more than in IOP1, the relative importance of the different dust mechanisms is the same. In both years, emission by cold pool outflows from deep convection causes most dust, followed by dust advection, monsoon surges, low‐level jet emission and lastly dry convective plumes. Given the dominance of cold pools, it is very important that they be incorporated in dust modeling efforts over the region. Because cold pools frequently occur at night and are associated with cloud cover, instruments that can monitor in these conditions are particularly valuable in this region. Sun photometer aerosol optical depth retrievals, for example, are only available for 23% (41%) of the time cold pool emission occurs at the supersite in IOP1 (IOP2). Deployment of instrumentation in remote regions being difficult and expensive, choosing the optimal instrument payload pays dividends. With this motivation, we evaluate the different dust detection instrumentation deployed at the supersite and develop an approach which can identify and characterize individual dust emission mechanisms with a high degree of success purely from routine meteorological observations and remote sensing. This identification is, however, much more challenging in the case of dust advection.

Relationship of MISR component AODs with black carbon and other ground monitored particulate matter composition

This study assessed the relationship between the satellite Aerosol Optical Depths (AODs) and the ground monitored concentrations of particulate matter (PM) mass and its major constituents (black carbon–BC, organic carbon–OC, sulfates and nitrates), respectively. Both component AOD and total AOD products of Multi–angel Imaging Spectro Radiometer (MISR) were used for comparison along with the AOD product of the Moderate Resolution Imaging Spectroradiometer (MODIS). The ground PM data available during the period from 2004 to 2010 at the Asian Institute of Technology (AIT), a suburb site of the Bangkok Metropolitan Region, was used. MODIS and MISR AODs were validated against Sun photometer AOD, monitored at the Pimai AERONET station which showed strong linear regression with high R2 values of 0.87 and 0.92, respectively. The correlation coefficients between MODIS and MISR AODs and PM mass concentrations, respectively, were improved after exclusion of observations with cloud cover above 3/10. The R values (square root of determination coefficient R2) for linear relationships between PM10 and MODIS AOD were accordingly increased from 0.33 to 0.58 for MODIS AOD and from 0.25 to 0.54 for MISR AOD, while those for PM2.5 were improved from 0.30 to 0.55 for MODIS AOD and from 0.31 to 0.43 for MISR AOD. The stepwise regression was conducted to analyze the relationship between MISR component AODs and the mass concentration of PM10 and PM2.5, respectively, as well as their constituents. Higher R values were obtained for all regression equations using MISR component AODs as compared to those using total AOD. MISR component AODs showed higher capacity for monitoring daily BC (R=0.74–0.75) and sulfates (R=0.72), as compared to nitrates (R=0.52–0.54) and hourly OC (R=0.47). The potential of MISR component AODs for ambient PM monitoring should be explored and applied in other regions.

Ceilometer calibration for retrieval of aerosol optical properties

Ceilometers are durable compact backscatter lidars widely used to detect cloud base height. They are also useful for measuring aerosols. We introduced a ceilometer (CL51) for observing dust in a source region in Mongolia. For retrieving aerosol profiles with a backscatter lidar, the molecular backscatter signal in the aerosol free heights or system constant of the lidar is required. Although the system constant of the ceilometer is calibrated by the manufacturer, it is not necessarily accurate enough for the aerosol retrieval. We determined a correction factor, which is defined as the ratio of true attenuated backscattering coefficient to the measured attenuated backscattering coefficient, for the CL51 ceilometer using a dual-wavelength Mie-scattering lidar in Tsukuba, Japan before moving the ceilometer to Dalanzadgad, Mongolia. The correction factor determined by minimizing the difference between the ceilometer and lidar backscattering coefficients was approximately 1.2±0.1. Applying the correction to the CL51 signals, the aerosol optical depth (AOD) agreed well with the sky-radiometer AOD during the observation period (13–17 February 2013) in Tsukuba (9×10−3 of mean square error). After moving the ceilometer to Dalanzadgad, however, the AOD observed with the CL51 (calibrated by the correction factor determined in Tsukuba) was approximately 60% of the AErosol RObotic NETwork (AERONET) sun photometer AOD. The possible causes of the lower AOD results are as follows: (1) the limited height range of extinction integration (<3km); (2) change in the correction factor during the ceilometer transportation or with the window contamination in Mongolia. In both cases, on-site calibrations by dual-wavelength lidar are needed. As an alternative method, we showed that the backward inversion method was useful for retrieving extinction coefficients if the AOD was larger than 1.5. This retrieval method does not require the system constant and molecular backscatter signals, and can be applied to severe dust and air pollution aerosol cases in East Asia.