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25 pages, 12987 KiB

Open AccessArticle

Characteristic and Driving Factors of Aerosol Optical Depth over Mainland China during 1980–2017

by Wenmin Qin, Ying Liu, Lunche Wang, Aiwen Lin, Xiangao Xia, Huizheng Che, Muhammad Bilal and Ming Zhang

Remote Sens. 2018, 10(7), 1064; https://doi.org/10.3390/rs10071064 - 5 Jul 2018

Cited by 88 | Viewed by 6076

Abstract

Since the reform and opening up of China, the increasing aerosol emissions have posted great challenges to the country’s climate change and human health. The aerosol optical depth (AOD) is one of the main physical indicators quantifying the atmospheric turbidity and air pollution. [...] Read more.

Since the reform and opening up of China, the increasing aerosol emissions have posted great challenges to the country’s climate change and human health. The aerosol optical depth (AOD) is one of the main physical indicators quantifying the atmospheric turbidity and air pollution. In this study, 38-years (1980–2017) of spatial and temporal variations of AOD in China were analyzed using AOD records derived from MODIS atmosphere products and the MERRA-2 dataset. The results showed that the annual mean AOD values throughout China have gone through an increasing, but fluctuating, trend, especially in 1982 and in 1992 due to two volcano eruptions; the AOD values experienced a dramatically increasing period during 2000–2007 with the rapid economic development and “population explosions” in China/after 2008, the AOD values gradually decreased from 0.297 (2008) to 0.257 (2017). The AOD values in China were generally higher in spring than that in other seasons. The Sichuan Basin has always been an area with high AOD values owing to the strong human activity and the basin topography (hindering aerosol diffusions in the air). In contrast, the Qinghai Tibet Plateau has always been an area with low AOD values due to low aerosol emissions and clear sky conditions there. The trend analysis of AOD values during 1980–2017 in China indicated that the significant increasing trend was mainly observed in Southeastern China. By contrast, the AOD values in the northernmost of China showed a significant decreasing trend. Then, the contributions (AODP) of the AOD for black carbon aerosol (BCAOD), dust aerosol (DUAOD), organic carbon aerosol (OCAOD), sea salt aerosol (SSAOD), and SO₄ aerosol (SO₄AOD) to the total AOD values were calculated. The results showed that DUAOD (25.43%) and SO₄AOD (49.51%) were found to be the main driving factors for the spatial and temporal variations of AOD values. Finally, the effects of anthropogenic aerosol emissions, socioeconomic factors, and land-use and land coverage changes on AOD were analyzed. The GDP, population density, and passenger traffic volume were found to be the main socioeconomic drivers for AOD distributions. Relatively larger AOD values were mainly found in urban land and land covered by water, while lower AOD values were found in grassland and permanent glacier areas. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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17 pages, 1550 KiB

Open AccessArticle

Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM_2.5 in the Northeastern USA

by Allan C. Just, Margherita M. De Carli, Alexandra Shtein, Michael Dorman, Alexei Lyapustin and Itai Kloog

Remote Sens. 2018, 10(5), 803; https://doi.org/10.3390/rs10050803 - 22 May 2018

Cited by 69 | Viewed by 8847

Abstract

Satellite-derived estimates of aerosol optical depth (AOD) are key predictors in particulate air pollution models. The multi-step retrieval algorithms that estimate AOD also produce quality control variables but these have not been systematically used to address the measurement error in AOD. We compare [...] Read more.

Satellite-derived estimates of aerosol optical depth (AOD) are key predictors in particulate air pollution models. The multi-step retrieval algorithms that estimate AOD also produce quality control variables but these have not been systematically used to address the measurement error in AOD. We compare three machine-learning methods: random forests, gradient boosting, and extreme gradient boosting (XGBoost) to characterize and correct measurement error in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) 1 × 1 km AOD product for Aqua and Terra satellites across the Northeastern/Mid-Atlantic USA versus collocated measures from 79 ground-based AERONET stations over 14 years. Models included 52 quality control, land use, meteorology, and spatially-derived features. Variable importance measures suggest relative azimuth, AOD uncertainty, and the AOD difference in 30–210 km moving windows are among the most important features for predicting measurement error. XGBoost outperformed the other machine-learning approaches, decreasing the root mean squared error in withheld testing data by 43% and 44% for Aqua and Terra. After correction using XGBoost, the correlation of collocated AOD and daily PM_2.5 monitors across the region increased by 10 and 9 percentage points for Aqua and Terra. We demonstrate how machine learning with quality control and spatial features substantially improves satellite-derived AOD products for air pollution modeling. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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19 pages, 10924 KiB

Open AccessEditor’s ChoiceArticle

Preliminary Investigation of a New AHI Aerosol Optical Depth (AOD) Retrieval Algorithm and Evaluation with Multiple Source AOD Measurements in China

by Fukun Yang, Yang Wang, Jinhua Tao, Zifeng Wang, Meng Fan, Gerrit De Leeuw and Liangfu Chen

Remote Sens. 2018, 10(5), 748; https://doi.org/10.3390/rs10050748 - 14 May 2018

Cited by 34 | Viewed by 6594

Abstract

The Himawari-8 geostationary weather satellite, which is an Earth observing satellite launched in October 2014, has been applied in climate, environment, and air quality studies. Using hourly observation data from the Advanced Himawari Imager (AHI) on board Himawari-8, a new dark target algorithm [...] Read more.

The Himawari-8 geostationary weather satellite, which is an Earth observing satellite launched in October 2014, has been applied in climate, environment, and air quality studies. Using hourly observation data from the Advanced Himawari Imager (AHI) on board Himawari-8, a new dark target algorithm was proposed to retrieve the aerosol optical depth (AOD) at 1 km and 5 km resolutions over mainland China. Because of the short satellite operation time and lack of AErosol RObotic NETwork (AERONET) sites across China, we cannot derive robust and representative surface reflectance relationships for the visible to near-infrared channels by atmospheric correction. Therefore, we inherited the empirical reflectance relationship from the Moderate Resolution Imaging Spectroradiometer (MODIS) and we used the AHI and MODIS spectral response functions to make the relationship more suitable for AHI. Ultimately, our AOD products can better reflect the regional characteristics with the AHI sensor. Seasonal averages showed that our product is more similar to MODIS Collection 6 (C6) Dark Target (DT) AOD than the Japan Aerospace Exploration Agency (JAXA) AHI AOD, but the difference is largest in winter. In addition, we evaluated several satellite retrieval products (our AHI AOD, JAXA AHI AOD, the National Oceanic and Atmospheric Administration (NOAA) VIIRS AOD, MODIS DT AOD, and MODIS DB AOD) against AERONET AOD from July 2016 to June 2017. The results showed that our AHI measurements demonstrate good agreement with, but exhibit a little overestimation, as compared to ground-based AERONET measurements with a correlation coefficient of 0.83 and an root-mean-square error (RMSE) of 0.112. The hourly validation also showed stable statistical results. A time series comparison with ground-based observations from two AERONET sites (Beijing-CAMS and XiangHe) showed that our AHI AOD products have trends as those in MODIS DB AOD, but that the bias in Beijing-CAMS is positive and higher than that in XiangHe. This error and the slight overestimation may be caused by the single continental aerosol model assumption and not considering the Normalized Difference Vegetation Index (NDVI). Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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17 pages, 54667 KiB

Open AccessArticle

Haze Optical Properties from Long-Term Ground-Based Remote Sensing over Beijing and Xuzhou, China

by Kai Qin, Luyao Wang, Jian Xu, Husi Letu, Kefei Zhang, Ding Li, Jiaheng Zou and Wenzhi Fan

Remote Sens. 2018, 10(4), 518; https://doi.org/10.3390/rs10040518 - 26 Mar 2018

Cited by 19 | Viewed by 6066

Abstract

Aerosol haze pollution has had a significant impact on both global climate and the regional air quality of Eastern China, which has a high proportion of high level pollution days. Statistical analyses of aerosol optical properties and direct radiative forcing at two AERONET [...] Read more.

Aerosol haze pollution has had a significant impact on both global climate and the regional air quality of Eastern China, which has a high proportion of high level pollution days. Statistical analyses of aerosol optical properties and direct radiative forcing at two AERONET sites (Beijing and Xuzhou) were conducted from 2013 to 2016. Results indicate: (1) Haze pollution days accounted for 26% and 20% of days from 2013 to 2016 in Beijing and Xuzhou, respectively, with the highest proportions in winter; (2) The averaged aerosol optical depth (AOD) at 550 nm on haze days were about 3.7 and 1.6 times greater than those on clean days in Beijing and Xuzhou, respectively. At both sites, the maximum AOD occurred in summer; (3) Hazes were dominated by fine particles at both sites. However, as compared to Xuzhou, Beijing had larger coarse mode AOD and higher percentage of small α. This data, together with an analysis of size distribution, suggests that the hazes in Beijing were more susceptible to coarse dust particles than Xuzhou; (4) During hazes in Beijing, the single scattering albedo (SSA) is significantly higher when compared to clean conditions (0.874 vs. 0.843 in SSA_{440 nm}), an increase much less evident in Xuzhou. The most noticeable differences in both SSA and the imaginary part of the complex refractive index between Beijing and Xuzhou were found in winter; (5) In Beijing, the haze radiative forcing produced an averaged cooling effect of −113.6 ± 63.7 W/m² at the surface, whereas the averaged heating effect of 77.5 ± 49.7 W/m² within the atmosphere was at least twice as strong as clean days. In Xuzhou, such a radiative forcing effect appeared to be much smaller and the difference between haze and clean days was insignificant. Derived from long-term observation, these findings are more significant for the improvement of our understanding of haze formation in China and the assessment of its impacts on radiative forcing of climate change than previous short-term case studies. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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28 pages, 5385 KiB

Open AccessArticle

Modification of Local Urban Aerosol Properties by Long-Range Transport of Biomass Burning Aerosol

by Iwona S. Stachlewska, Mateusz Samson, Olga Zawadzka, Kamila M. Harenda, Lucja Janicka, Patryk Poczta, Dominika Szczepanik, Birgit Heese, Dongxiang Wang, Karolina Borek, Eleni Tetoni, Emmanouil Proestakis, Nikolaos Siomos, Anca Nemuc, Bogdan H. Chojnicki, Krzysztof M. Markowicz, Aleksander Pietruczuk, Artur Szkop, Dietrich Althausen, Kerstin Stebel, Dirk Schuettemeyer and Claus Zehner Show full author list Hide full author list

Remote Sens. 2018, 10(3), 412; https://doi.org/10.3390/rs10030412 - 7 Mar 2018

Cited by 39 | Viewed by 9502

Abstract

During August 2016, a quasi-stationary high-pressure system spreading over Central and North-Eastern Europe, caused weather conditions that allowed for 24/7 observations of aerosol optical properties by using a complex multi-wavelength PollyXT lidar system with Raman, polarization and water vapour capabilities, based at the [...] Read more.

During August 2016, a quasi-stationary high-pressure system spreading over Central and North-Eastern Europe, caused weather conditions that allowed for 24/7 observations of aerosol optical properties by using a complex multi-wavelength PollyXT lidar system with Raman, polarization and water vapour capabilities, based at the European Aerosol Research Lidar Network (EARLINET network) urban site in Warsaw, Poland. During 24–30 August 2016, the lidar-derived products (boundary layer height, aerosol optical depth, Ångström exponent, lidar ratio, depolarization ratio) were analysed in terms of air mass transport (HYSPLIT model), aerosol load (CAMS data) and type (NAAPS model) and confronted with active and passive remote sensing at the ground level (PolandAOD, AERONET, WIOS-AQ networks) and aboard satellites (SEVIRI, MODIS, CATS sensors). Optical properties for less than a day-old fresh biomass burning aerosol, advected into Warsaw’s boundary layer from over Ukraine, were compared with the properties of long-range transported 3–5 day-old aged biomass burning aerosol detected in the free troposphere over Warsaw. Analyses of temporal changes of aerosol properties within the boundary layer, revealed an increase of aerosol optical depth and Ångström exponent accompanied by an increase of surface PM₁₀ and PM_2.5. Intrusions of advected biomass burning particles into the urban boundary layer seem to affect not only the optical properties observed but also the top height of the boundary layer, by moderating its increase. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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21 pages, 6758 KiB

Open AccessArticle

Three-Dimensional Physical and Optical Characteristics of Aerosols over Central China from Long-Term CALIPSO and HYSPLIT Data

by Xin Lu, Feiyue Mao, Zengxin Pan, Wei Gong, Wei Wang, Liqiao Tian and Shenghui Fang

Remote Sens. 2018, 10(2), 314; https://doi.org/10.3390/rs10020314 - 18 Feb 2018

Cited by 32 | Viewed by 6687

Abstract

Aerosols greatly influence global and regional atmospheric systems, and human life. However, a comprehensive understanding of the source regions and three-dimensional (3D) characteristics of aerosol transport over central China is yet to be achieved. Thus, we investigate the 3D macroscopic, optical, physical, and [...] Read more.

Aerosols greatly influence global and regional atmospheric systems, and human life. However, a comprehensive understanding of the source regions and three-dimensional (3D) characteristics of aerosol transport over central China is yet to be achieved. Thus, we investigate the 3D macroscopic, optical, physical, and transport properties of the aerosols over central China based on the March 2007 to February 2016 data obtained from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model. Our results showed that approximately 60% of the aerosols distributed over central China originated from local areas, whereas non-locally produced aerosols constituted approximately 40%. Anthropogenic aerosols constituted the majority of the aerosol pollutants (69%) that mainly distributed less than 2.0 km above mean sea level. Natural aerosols, which are mainly composed of dust, accounted for 31% of the total aerosols, and usually existed at an altitude higher than that of anthropogenic aerosols. Aerosol particles distributed in the near surface were smaller and more spherical than those distributed above 2.0 km. Aerosol optical depth (AOD) and the particulate depolarization ratio displayed decreasing trends, with a total decrease of 0.11 and 0.016 from March 2007 to February 2016, respectively. These phenomena indicate that during the study period, the extinction properties of aerosols decreased, and the degree of sphericity in aerosol particles increased. Moreover, the annual anthropogenic and natural AOD demonstrated decreasing trends, with a total decrease of 0.07 and 0.04, respectively. This study may benefit the evaluation of the effects of the 3D properties of aerosols on regional climates. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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19 pages, 30570 KiB

Open AccessArticle

Aerosol Optical Depth Retrieval over East Asia Using Himawari-8/AHI Data

by Wenhao Zhang, Hui Xu and Fengjie Zheng

Remote Sens. 2018, 10(1), 137; https://doi.org/10.3390/rs10010137 - 19 Jan 2018

Cited by 52 | Viewed by 8247

Abstract

This paper presents a new algorithm to retrieve the aerosol optical depth (AOD) from a Himawari-8 Advanced Himawari Imager (AHI). Six typical aerosol models that derived from the long-term ground-based observations of East Asia are used in AOD retrieval. To accurately determine the [...] Read more.

This paper presents a new algorithm to retrieve the aerosol optical depth (AOD) from a Himawari-8 Advanced Himawari Imager (AHI). Six typical aerosol models that derived from the long-term ground-based observations of East Asia are used in AOD retrieval. To accurately determine the surface reflectance, improved channel relationships between red, blue, and shortwave infrared (SWIR) are built up according to the infrared Normalized Difference Vegetation Index (NDVI_SWIR). Based on the new derived aerosol models and improved channel relationships, AOD over East Asian is retrieved by using the AHI data. The results are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products (MOD04 and MYD04) and yielded a correlation coefficient lager than 0.8 (R = 0.87 and 0.92, respectively). In addition, the retrieved AOD values are also validated by ground-based measurements at 12 Aerosol Robotic Network (AERONET) locations and revealed a good agreement between them (R = 0.86). Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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4859 KiB

Open AccessArticle

Mini N₂-Raman Lidar Onboard Ultra-Light Aircraft for Aerosol Measurements: Demonstration and Extrapolation

by Patrick Chazette and Julien Totems

Remote Sens. 2017, 9(12), 1226; https://doi.org/10.3390/rs9121226 - 28 Nov 2017

Cited by 11 | Viewed by 5657

Abstract

Few airborne aerosol research experiments have deployed N₂-Raman Lidar despite its capability to retrieve aerosol optical properties without ambiguity. Here, we show the high scientific potential of this instrument when used with specific flight plans. Our demonstration is based on (i) [...] Read more.

Few airborne aerosol research experiments have deployed N₂-Raman Lidar despite its capability to retrieve aerosol optical properties without ambiguity. Here, we show the high scientific potential of this instrument when used with specific flight plans. Our demonstration is based on (i) a field-experiment conducted in June 2015 in southern France, involving a N₂-Raman Lidar embedded on an ultra-light aircraft (ULA); and (ii) an appropriate algorithmic approach using two-level flight levels, aiming to solve the notorious instability of the airborne Lidar inversion for the retrieval of aerosol optical properties. The Lidar measurements include the determination of the aerosol extinction coefficient along ~500 m horizontal line of sight, and this value is used as a reference to validate the proposed algorithm. The Lidar-derived vertical profiles obtained during the flights are used as an input in a Monte Carlo simulation in order to compute the error budget in terms of biases and standard deviations on the retrieved aerosol extinction coefficient profile, as well as the subsequent optical thickness. The influence of the Lidar ratio (i.e., between aerosol extinction and backscatter) on the error budget is further discussed. Finally, from this end-to-end modeling, an optimal N₂-Raman Lidar is proposed for airborne experiments, adapted to both small and large carriers. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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11205 KiB

Open AccessArticle

Effect of Heat Wave Conditions on Aerosol Optical Properties Derived from Satellite and Ground-Based Remote Sensing over Poland

by Iwona S. Stachlewska, Olga Zawadzka and Ronny Engelmann

Remote Sens. 2017, 9(11), 1199; https://doi.org/10.3390/rs9111199 - 22 Nov 2017

Cited by 28 | Viewed by 7455

Abstract

During an exceptionally warm September in 2016, unique and stable weather conditions contributed to a heat wave over Poland, allowing for observations of aerosol optical properties, using a variety of ground-based and satellite remote sensors. The data set collected during 11–16 September 2016 [...] Read more.

During an exceptionally warm September in 2016, unique and stable weather conditions contributed to a heat wave over Poland, allowing for observations of aerosol optical properties, using a variety of ground-based and satellite remote sensors. The data set collected during 11–16 September 2016 was analysed in terms of aerosol transport (HYbrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT)), aerosol load model simulations (Copernicus Atmosphere Monitoring Service (CAMS), Navy Aerosol Analysis and Prediction System (NAAPS), Global Environmental Multiscale-Air Quality (GEM-AQ), columnar aerosol load measured at ground level (Aerosol Robotic NETwork (AERONET), Polish Aerosol Research Network (PolandAOD)) and from satellites (Spinning Enhanced Visible and Infrared Imager (SEVIRI), Moderate Resolution Imaging Spectroradiometer (MODIS)), as well as with 24/7 PollyXT Raman Lidar observations at the European Aerosol Research Lidar Network (EARLINET) site in Warsaw. Analyses revealed a single day of a relatively clean background aerosol related to an Arctic air-mass inflow, surrounded by a few days with a well increased aerosol load of differing origin: pollution transported from Germany and biomass burning from Ukraine. Such conditions proved excellent to test developed-in-house algorithms designed for near real-time aerosol optical depth (AOD) derivation from the SEVIRI sensor. The SEVIRI AOD maps derived over the territory of Poland, with an exceptionally high resolution (every 15 min; 5.5 × 5.5 km²), revealed on an hourly scale, very low aerosol variability due to heat wave conditions. Comparisons of SEVIRI with NAAPS and CAMS AOD maps show strong qualitative similarities; however, NAAPS underestimates AOD and CAMS tends to underestimate it on relatively clean days (<0.2), and overestimate it for a high aerosol load (>0.4). A slight underestimation of the SEVIRI AOD is reported for pixel-to-column comparisons with AODs of several radiometers (AERONET, PolandAOD) and Lidar (EARLINET) with high correlation coefficients (r² of 0.8–0.91) and low root-mean-square error (RMSE of 0.03–0.05). A heat wave driven increase of the boundary layer height of 10% is accompanied with the AOD increase of 8–12% for an urban site dominated by anthropogenic pollution. Contrary trend, with an AOD decrease of around 4% for a rural site dominated by a long-range transported biomass burning aerosol is reported. There is a positive feedback of heat wave conditions on local and transported pollution and an extenuating effect on transported biomass burning aerosol. The daytime mean SEVIRI PM2.5 converted from the SEVIRI AODs at a pixel representative for Warsaw is in agreement with the daily mean PM2.5 surface measurements, whereby SEVIRI PM2.5 and Lidar-derived Ångström exponent are anti-correlated. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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6282 KiB

Open AccessArticle

An Evaluation of Four MODIS Collection 6 Aerosol Products in a Humid Subtropical Region

by Ming Zhang, Bo Huang and Qingqing He

Remote Sens. 2017, 9(11), 1173; https://doi.org/10.3390/rs9111173 - 16 Nov 2017

Cited by 11 | Viewed by 4377

Abstract

Moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) products have been widely used to characterize the temporal variations and spatial distributions of atmospheric aerosols. In the present study, we evaluate the performance of four Terra and Aqua MODIS Collection 6 (C6) quality [...] Read more.

Moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) products have been widely used to characterize the temporal variations and spatial distributions of atmospheric aerosols. In the present study, we evaluate the performance of four Terra and Aqua MODIS Collection 6 (C6) quality assured AOD products in the Pearl River Delta (PRD) region, a humid subtropical region. The 10 km AOD products retrieved by the Dark Target (DT) and Deep Blue (DB) algorithms, the merged DT/DB (DTDB) 10 km product, and the DT 3 km AOD product were obtained for 2006–2015. These products were compared with Aerosol Robotic Network (AERONET) observations, and with each other. The Terra- and Aqua-derived AODs are quantitatively similar. However, there are significant differences among the four AOD products. The DT 10 km product correlates more closely with AERONET AOD observations than does the DB 10 km product. The latter tends to underestimate the AOD, whereas the former typically overestimates it for highly urbanized areas. The DTDB 10 km product is mainly derived from the DT 10 km product; it does not provide a gap-filled data set, because valid DB 10 km retrievals are not included in the merged product even when DT 10 km retrievals are unavailable. Therefore, the DT/DB merging protocol should be improved. The DT 3 km AOD product closely mimics the DT 10 km product; however, it contains fewer data than the DT 10 km product over water-contaminated areas. In addition, although the quality assured AOD products are recommended for use in quantitative applications by the MODIS aerosol science team, the sampling frequency of these products is generally lower than 25%. Thus, the sampling issues of these products should be considered in humid subtropical areas. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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10259 KiB

Open AccessArticle

Long-Term, High-Resolution Survey of Atmospheric Aerosols over Egypt with NASA’s MODIS Data

by Mohammed Shokr, Muhammed El-Tahan, Alaa Ibrahim, Allison Steiner and Nashaat Gad

Remote Sens. 2017, 9(10), 1027; https://doi.org/10.3390/rs9101027 - 6 Oct 2017

Cited by 20 | Viewed by 7301

Abstract

A decadal survey of atmospheric aerosols over Egypt and selected cities and regions is presented using daily aerosol optical depth (AOD) data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) at 550 nm wavelength onboard the Aqua satellite. We explore the AOD spatio-temporal variations [...] Read more.

A decadal survey of atmospheric aerosols over Egypt and selected cities and regions is presented using daily aerosol optical depth (AOD) data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) at 550 nm wavelength onboard the Aqua satellite. We explore the AOD spatio-temporal variations over Egypt during a 12-year record (2003 to 2014) using the MODIS high-resolution (10 km) Level 2 data product. Five cities and two geographic regions that feature different landscape and human activities were selected for detailed analysis. For most of the examined areas, AOD is found to be most frequent in the 0.2–0.3 range, and the highest mean AOD was found to be over Cairo, Alexandria, and the Nile Delta region. Severe events are identified based on AOD higher than a selected threshold. Most of these events are engendered by sand and dust storms that originate from the Western Desert during January–April. Spatial analysis indicates that they cover the Nile Delta region, including cities of Cairo and Alexandria, on the same day. Examination of the spatial gradient of AOD along the four cardinal directions originating from the city’s center reveals seasonally dependent gradients in some cases. The gradients have been linked to locations of industrial activity. No trend of AOD has been observed in the studied areas during the study period, though data from Cairo and Asyut reveal a slight linear increase of AOD. Considering Cairo is commonly perceived as a city of poor air quality, the results show that local events are fairly constrained. The study highlights spatial and seasonal distributions of AOD and links them to geographic and climatic conditions across the country. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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4869 KiB

Open AccessArticle

Remote Sensing of Aerosol Optical Depth Using an Airborne Polarimeter over North China

by Han Wang, Leiku Yang, Anjian Deng, Weibing Du, Pei Liu and Xiaobing Sun

Remote Sens. 2017, 9(10), 979; https://doi.org/10.3390/rs9100979 - 22 Sep 2017

Cited by 9 | Viewed by 4916

Abstract

The airborne Atmosphere Multi-angle Polarization Radiometer (AMPR) was employed to perform airborne measurements over North China between 2012 and 2016. Seven flights and synchronous ground-based observations were acquired. These data were used to test the sensor’s measurements and associated aerosol retrieval algorithm. According [...] Read more.

The airborne Atmosphere Multi-angle Polarization Radiometer (AMPR) was employed to perform airborne measurements over North China between 2012 and 2016. Seven flights and synchronous ground-based observations were acquired. These data were used to test the sensor’s measurements and associated aerosol retrieval algorithm. According to the AMPR measurements, a successive surface-atmosphere decoupling based algorithm was developed to retrieve the aerosol optical depth (AOD). It works via an iteration method, and the lookup table was employed in the aerosol inversion. Throughout the results of the AMPR retrievals, the surface polarized reflectances derived from air- and ground-based instruments were well matched; the measured and simulated reflectances at the aircraft level, which were simulated based on in situ sun photometer observed aerosol properties, were in good agreement; and the AOD measurements were validated against the automatic sun-photometer (CE318) at the nearest time and location. The AOD results were close; the average deviation was less than 0.03. The MODIS AODs were also employed to test the AMPR retrievals, and they showed the same trend. These results illustrate that (i) the successive surface-atmosphere decoupling method in the retrieved program completed its mission and (ii) the aerosol retrieval method has its rationality and potential ability in the regionally accurate remote sensing of aerosol. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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6221 KiB

Open AccessArticle

Raman Lidar Observations of Aerosol Optical Properties in 11 Cities from France to Siberia

by Elsa Dieudonné, Patrick Chazette, Fabien Marnas, Julien Totems and Xiaoxia Shang

Remote Sens. 2017, 9(10), 978; https://doi.org/10.3390/rs9100978 - 22 Sep 2017

Cited by 18 | Viewed by 5342

Abstract

In June 2013, a ground-based mobile lidar performed the ~10,000 km ride from Paris to Ulan-Ude, near Lake Baikal, profiling aerosol optical properties in the cities visited along the journey and allowing the first comparison of urban aerosols optical properties across Eurasia. The [...] Read more.

In June 2013, a ground-based mobile lidar performed the ~10,000 km ride from Paris to Ulan-Ude, near Lake Baikal, profiling aerosol optical properties in the cities visited along the journey and allowing the first comparison of urban aerosols optical properties across Eurasia. The lidar instrument was equipped with N₂-Raman and depolarization channels, enabling the retrieval of the 355-nm extinction-to-backscatter ratio (also called Lidar Ratio (LR)) and the linear Particle Depolarization Ratio (PDR) in the urban planetary boundary or residual layer over 11 cities. The optical properties of pollution particles were found to be homogeneous all along the journey: no longitude dependence was observed for the LR, with most values falling within the 67–96 sr range. There exists only a slight increase of PDR between cities in Europe and Russia, which we attribute to a higher fraction of coarse terrigenous particles lifted from bad-tarmac roads and unvegetated terrains, which resulted, for instance, in a +1.7% increase between the megalopolises of Paris and Moscow. A few lower LR values (38 to 50 sr) were encountered above two medium size Siberian cities and in an isolated plume, suggesting that the relative weight of terrigenous aerosols in the mix may increase in smaller cities. Space-borne observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), retrieved during summer 2013 above the same Russian cities, confirmed the prevalence of aerosols classified as “polluted dust”. Finally, we encountered one special feature in the Russian aerosol mix as we observed with good confidence an unusual aerosol layer displaying both a very high LR (96 sr) and a very high PDR (20%), even though both features make it difficult to identify the aerosol type. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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3220 KiB

Open AccessArticle

Characteristics of Aerosol Types in Beijing and the Associations with Air Pollution from 2004 to 2015

by Yang Ou, Wenhui Zhao, Junqian Wang, Wenji Zhao and Bo Zhang

Remote Sens. 2017, 9(9), 898; https://doi.org/10.3390/rs9090898 - 30 Aug 2017

Cited by 23 | Viewed by 5888

Abstract

With the fast development of the economy and expansion, a large number of people have concentrated in Beijing over the past few decades, leading to the result that Beijing has become home to one of the most complex mixtures of aerosol types in [...] Read more.

With the fast development of the economy and expansion, a large number of people have concentrated in Beijing over the past few decades, leading to the result that Beijing has become home to one of the most complex mixtures of aerosol types in the world. The various aerosol types play different roles in the determination of global climate change, visibility, and human health. However, to the best of our knowledge, research has rarely analyzed the correlation between aerosol types and air quality index (AQI) in Beijing (urban and suburban) over a long-term series of observations. Therefore, in this study, we aim to identify and discuss the different aerosol types and AQI in Beijing from 2004 to 2015. The aerosol types are classified into six categories: dust, mixed, highly-absorbing, moderately-absorbing, slightly-absorbing, and scattering by a multiple clustering method with the fine mode fraction (FMF) and single scattering albedo (SSA) data of retrievals from the global Aerosol Robotic Network (AERONET) sun photometer sites. The AQI levels: are good (0–50); moderate (51–100); unhealthy for sensitive groups (101–150); unhealthy (151–200); very unhealthy (201–300); and hazardous (>300). The results show that a significant FMF variability occurred among different seasons in Beijing, with maximum values present in spring and minimum values in winter. The SSA values exhibit variation, with small fluctuations from season to season. In the case of BJ station, the scattering aerosols are more frequent in summer (39%) and less in winter (1%), while the coarse particles (dust) are more frequent in spring (18%) and less in autumn (6%). In contrast, the absorbing aerosols (especially slightly-absorbing) are more frequent in summer (35%) and winter (15%). However, the mixed aerosol types are more frequent in spring (38%) and less in summer (8%). There is a similar seasonal variation in XH. In the past 12 years, the slightly-absorbing aerosol type in Beijing has increased by approximately 14%, which is believed to be due to the rapid development of industrial cities. In addition, comparing the urban and suburban regions, the slightly-absorbing aerosol type is the dominant aerosol type in both areas. Furthermore, to identify the dominant aerosol types which lead to air pollution, a related analysis was carried out by analyzing different aerosol types and the relationship between aerosol types and AQI. The results indicate that the air pollution was strongly correlated to slightly-absorbing aerosols, in which the percentage of slightly-absorbing aerosols was about 49% during the hazardous days in 2013–2015, and the correlation between AQI and aerosol types is also strong (R² = 0.76 and 0.97, in Beijing and Xianghe). Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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Open AccessArticle

North Africa and Saudi Arabia Day/Night Sandstorm Survey (NASCube)

by Louis Gonzalez and Xavier Briottet

Remote Sens. 2017, 9(9), 896; https://doi.org/10.3390/rs9090896 - 30 Aug 2017

Cited by 19 | Viewed by 7563

Abstract

The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASCube) [...] Read more.

The Meteosat Second Generation (MSG) geostationary platform equipped with the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument provides observations of the Earth every 15 min since 2004. Based on those measurements, we present a new method called North African Sandstorm Survey (NASCube) to: (i) generate day/night remote sensing images in order to detect sandstorms over the Sahara and Saudi Arabia; and (ii) estimate day and night aerosol optical depth (AOD). This paper presents a method to create true color day and night images from the SEVIRI instrument level 1.5 products and the complete operational data processing system to detect sandstorms and quantify the AOD over the desert areas of North Africa and Saudi Arabia. The designed retrieval algorithms are essentially based on the use of artificial neural networks (ANN), which seems to be well suited to this issue. Our methods are validated against two different datasets, namely the Deep Blue NASA moderate-resolution imaging spectroradiometer (MODIS) product and AErosol RObotic NETwork (AERONET) acquisitions located in desert areas. It is shown that NASCube products deliver better estimations for high AOD (>0.2) over land areas than Deep Blue products. The open-public web platform will help researchers to identify, quantify and retrieve the impact of sandstorms over desert regions. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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Open AccessArticle

Estimation of Satellite-Based SO₄²⁻ and NH₄⁺ Composition of Ambient Fine Particulate Matter over China Using Chemical Transport Model

by Yidan Si, Shenshen Li, Liangfu Chen, Chao Yu and Wende Zhu

Remote Sens. 2017, 9(8), 817; https://doi.org/10.3390/rs9080817 - 9 Aug 2017

Cited by 11 | Viewed by 5776

Abstract

Epidemiologic and health impact studies have examined the chemical composition of ambient PM_2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM_2.5 data, sulfate and ammonium levels were [...] Read more.

Epidemiologic and health impact studies have examined the chemical composition of ambient PM_2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM_2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM_2.5 data with a spatial resolution of 0.1 × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of −35.9%, NME of 48.2%, ARB_50% of 53.68% for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO₄²⁻ and NH₄⁺ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO₄²⁻: −0.61%; NH₄⁺: −0.21%), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004–2007 and 2008–2011, followed by a negative trend over the period 2012–2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as follows: winter > summer > autumn > spring. High concentrations of these species were concentrated in the NCP and SCB, originating from coal-fired power plants and agricultural activities, respectively. Efforts to reduce sulfur dioxide (SO₂) emissions have yielded remarkable results since the government has adopted stricter control measures in recent years. Moreover, ammonia emissions should be controlled while reducing the concentration of sulfur, nitrogen and particulate matter. This study provides an assessment of the population’s exposure to certain chemical components. Full article

(This article belongs to the Special Issue Aerosol Remote Sensing)

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