scholarly journals Spatiotemporal Distribution of Major Aerosol Types over China Based on MODIS Products between 2008 and 2017

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 703 ◽  
Author(s):  
Qi-Xiang Chen ◽  
Chun-Lin Huang ◽  
Yuan Yuan ◽  
Qian-Jun Mao ◽  
He-Ping Tan

Knowledge of aerosol-type distribution is critical to the evaluation of aerosol–climate effects. However, research on aerosol-type distribution covering all is limited. This study characterized the spatiotemporal distribution of major aerosol types over China by using MODerate resolution Imaging Spectroradiometer (MODIS) products from 2008 to 2017. Two aerosol-type classification methods were combined to achieve this goal. One was for relatively high aerosol load (AOD ≥ 0.2) using aerosol optical depth (AOD) and aerosol relative optical depth (AROD) and the other was for low aerosol load (AOD < 0.2) using land use and population density information, which assumed that aerosols are closely related to local emissions. Results showed that the dominant aerosol-type distribution has a distinct spatial and temporal pattern. In western China, background aerosols (mainly dust/desert dust and continent aerosol) dominate with a combined occurrence ratio over 70% and they have slight variations on seasonal scale. While in eastern China, the dominant aerosols show strong seasonal variations. Spatially, mixed aerosols dominate most parts of eastern China in spring due to the influence of long-range transported dust from Taklamakan and Gobi desert and urban/industry aerosols take place in summer due to strong photochemical reactions. Temporally, mixed and urban/industry aerosols co-dominate eastern China.

2021 ◽  
Author(s):  
Zhujun Li ◽  
David Painemal ◽  
Gregory Schuster ◽  
Marian Clayton ◽  
Richard Ferrare ◽  
...  

Abstract. We assess the CALIPSO Version 4.2 (V4) aerosol typing and assigned lidar ratios over ocean using aerosol optical depth (AOD) retrievals from the Synergized Optical Depth of Aerosols (SODA) algorithm and retrieved columnar lidar ratio estimated by combining SODA AOD and CALIPSO attenuated backscatter (CALIPSO-SODA). Six aerosol types – clean marine, dusty marine, dust, polluted continental/smoke, polluted dust, and elevated smoke – are characterized using CALIPSO-SODA over ocean and the results are compared against the prescribed V4 lidar ratios, when only one aerosol type is present in the atmospheric column. For samples detected at 5-km or 20-km spatial resolutions and having AOD > 0.05, the CALIPSO-SODA lidar ratios are significantly different between different aerosol types, and are consistent with the type-specific values assigned in V4 to within 10 sr (except for polluted continental/smoke). This implies that the CALIPSO classification scheme generally categorizes aerosols correctly. We find remarkable daytime/nighttime regional agreement for clean marine aerosol over the open ocean (CALIPSO-SODA = 20–25 sr, V4 = 23 sr), elevated smoke over the southeast Atlantic (CALIPSO-SODA = 65–75 sr, V4 = 70 sr), and dust over the subtropical Atlantic adjacent to the African continent (CALIPSO-SODA = 40–50 sr, V4 = 44 sr). In contrast, daytime polluted continental/smoke lidar ratio is more than 20 sr smaller than the constant V4 vaue for that type, attributed in part to the challenge of classifying tenuous aerosol with low signal-to-noise ratio. Dust over most of the Atlantic Ocean features CALIPSO-SODA lidar ratios less than 40 sr, possibly suggesting the presence of dust mixed with marine aerosols or lidar ratio values that depend on source and evolution of the aerosol plume. The new dusty marine type introduced in V4 features similar magnitudes and spatial distribution as its clean marine counterpart with lidar ratio differences of less than 3 sr, and nearly identical values over the open ocean, implying that some modification of the classification scheme for the marine subtypes is warranted.


2020 ◽  
Author(s):  
Antonin Zabukovec ◽  
Gerard Ancellet ◽  
Iwan E. Penner ◽  
Mikhail Arshinov ◽  
Valery Kozlov ◽  
...  

Abstract. Airborne backscatter lidar measurements at 532 nm were carried out over Siberia in July 2013 and June 2017. The Russian Tu-134 flew over major Siberian cities (Novosibirsk, Tomsk, Krasnoyarsk, Yakutsk), the gas flaring fields of the Ob valley and Siberian Taiga in order to sample several kinds of Siberian aerosol sources. Aerosol types are derived using the Lagrangian FLEXible PARTicle dispersion model (FLEXPART) simulations, Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD), Infrared Atmospheric Sounding Interferometer (IASI) CO total column and AOD at 10 μm. Forest fire detection is based on NASA Fire Information for Resource Management System (FIRMS) from MODIS and the Visible Infrared Imaging Radiometer Suite (VIIRS) observations and airborne in-situ measurements when available. Six aerosol type could be identified in this work: (i) Dusty aerosol mixture (ii) Ob valley industrial emission (iii) fresh boreal forest fire plumes (iv) aged forest fire plumes (v) pollution over the Tomsk/Novosibirsk region (vi) long range transport of Chinese pollution over Yakutsk. The backscatter to extinction ratio and then the corresponding lidar ratio (LR) were derived for each of these 6 identified aerosol type, using an iterative method based on the Fernald forward inversion constrained by the 10 km MODIS collection 6 AOD distribution closed to the airborne lidar observation. The LR analysis showed that the lowest LR range was obtained for the Dusty Mix case (26–40 sr) and the highest for the urban and industrial pollution from the Tomsk/Novosibirsk area (71–90 sr). The comparison is good with previous estimate of LR according to the aerosol classification. The range of lidar ratio obtained for gas flaring emission (43–60 sr) was lower than the high values encountered in the Tomsk/Novosibirk urban area and has never been characterized using lidar observations. Airborne lidar backscatter ratio vertical structure, aerosol types and integrated LR derived from the airborne data analysis were compared to nearby CALIOP overpasses. These comparisons showed three main differences with the CALIOP LR and aerosol type classification over Siberia: (i) CALIOP aerosol layer can be classified as Elevated smoke instead of Polluted continental and vice versa, but with little influence on the LR value (ii) aging and transport of aerosol layers effect on the CALIOP LR value is not always properly accounted for even when the CALIOP classification is correct (iii) the lack of discrimination between fresh and old fire plume leads to an overestimation of the optical depth for the fresh fires in the CALIOP AOD over the fire source region.


2020 ◽  
Vol 12 (5) ◽  
pp. 881
Author(s):  
Qiaolin Zeng ◽  
Jinhua Tao ◽  
Liangfu Chen ◽  
Hao Zhu ◽  
SongYan Zhu ◽  
...  

Aerosol optical depth (AOD) has been widely used to estimate near-surface particulate matter (PM). In this study, ground-measured data from the Campaign on Atmospheric Aerosol Research network of China (CARE-China) and the Aerosol Robotic Network (AERONET) were used to evaluate the accuracy of Visible Infrared Imaging Radiometer Suite (VIIRS) AOD data for different aerosol types. These four aerosol types were from dust, smoke, urban, and uncertain and a fifth “type” was included for unclassified (i.e., total) aerosols. The correlation for dust aerosol was the worst (R2 = 0.15), whereas the correlations for smoke and urban types were better (R2 values of 0.69 and 0.55, respectively). The mixed-effects model was used to estimate the PM2.5 concentrations in Beijing–Tianjin–Hebei (BTH), Sichuan–Chongqing (SC), the Pearl River Delta (PRD), the Yangtze River Delta (YRD), and the Middle Yangtze River (MYR) using the classified aerosol type and unclassified aerosol type methods. The results suggest that the cross validation (CV) of different aerosol types has higher correlation coefficients than that of the unclassified aerosol type. For example, the R2 values for dust, smoke, urban, uncertain, and unclassified aerosol types BTH were 0.76, 0.85, 0.82, 0.82, and 0.78, respectively. Compared with the daily PM2.5 concentrations, the air quality levels estimated using the classified aerosol type method were consistent with ground-measured PM2.5, and the relative error was low (most RE was within ±20%). The classified aerosol type method improved the accuracy of the PM2.5 estimation compared to the unclassified method, although there was an overestimation or underestimation in some regions. The seasonal distribution of PM2.5 was analyzed and the PM2.5 concentrations were high during winter, low during summer, and moderate during spring and autumn. Spatially, the higher PM2.5 concentrations were predominantly distributed in areas of human activity and industrial areas.


2021 ◽  
Vol 13 (11) ◽  
pp. 2231
Author(s):  
Débora Souza Alvim ◽  
Júlio Barboza Chiquetto ◽  
Monica Tais Siqueira D’Amelio ◽  
Bushra Khalid ◽  
Dirceu Luis Herdies ◽  
...  

The scope of this work was to evaluate simulated carbon monoxide (CO) and aerosol optical depth (AOD) from the CAM-chem model against observed satellite data and additionally explore the empirical relationship of CO, AOD and fire radiative power (FRP). The simulated seasonal global concentrations of CO and AOD were compared, respectively, with the Measurements of Pollution in the Troposphere (MOPITT) and the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite products for the period 2010–2014. The CAM-chem simulations were performed with two configurations: (A) tropospheric-only; and (B) tropospheric with stratospheric chemistry. Our results show that the spatial and seasonal distributions of CO and AOD were reasonably reproduced in both model configurations, except over central China, central Africa and equatorial regions of the Atlantic and Western Pacific, where CO was overestimated by 10–50 ppb. In configuration B, the positive CO bias was significantly reduced due to the inclusion of dry deposition, which was not present in the model configuration A. There was greater CO loss due to the chemical reactions, and shorter lifetime of the species with stratospheric chemistry. In summary, the model has difficulty in capturing the exact location of the maxima of the seasonal AOD distributions in both configurations. The AOD was overestimated by 0.1 to 0.25 over desert regions of Africa, the Middle East and Asia in both configurations, but the positive bias was even higher in the version with added stratospheric chemistry. By contrast, the AOD was underestimated over regions associated with anthropogenic activity, such as eastern China and northern India. Concerning the correlations between CO, AOD and FRP, high CO is found during March–April–May (MAM) in the Northern Hemisphere, mainly in China. In the Southern Hemisphere, high CO, AOD, and FRP values were found during August–September–October (ASO) due to fires, mostly in South America and South Africa. In South America, high AOD levels were observed over subtropical Brazil, Paraguay and Bolivia. Sparsely urbanized regions showed higher correlations between CO and FRP (0.7–0.9), particularly in tropical areas, such as the western Amazon region. There was a high correlation between CO and aerosols from biomass burning at the transition between the forest and savanna environments over eastern and central Africa. It was also possible to observe the transport of these pollutants from the African continent to the Brazilian coast. High correlations between CO and AOD were found over southeastern Asian countries, and correlations between FRP and AOD (0.5–0.8) were found over higher latitude regions such as Canada and Siberia as well as in tropical areas. Higher correlations between CO and FRP are observed in Savanna and Tropical forests (South America, Central America, Africa, Australia, and Southeast Asia) than FRP x AOD. In contrast, boreal forests in Russia, particularly in Siberia, show a higher FRP x AOD correlation than FRP x CO. In tropical forests, CO production is likely favored over aerosol, while in temperate forests, aerosol production is more than CO compared to tropical forests. On the east coast of the United States, the eastern border of the USA with Canada, eastern China, on the border between China, Russia, and Mongolia, and the border between North India and China, there is a high correlation of CO x AOD and a low correlation between FRP with both CO and AOD. Therefore, such emissions in these regions are not generated by forest fires but by industries and vehicular emissions since these are densely populated regions.


2013 ◽  
Vol 6 (1) ◽  
pp. 1815-1858 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
M. A. Vaughan ◽  
A. H. Omar ◽  
R. R. Rogers ◽  
...  

Abstract. Aerosol classification products from the NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-1) on the NASA B200 aircraft are compared with coincident V3.01 aerosol classification products from the CALIOP instrument on the CALIPSO satellite. For CALIOP, aerosol classification is a key input to the aerosol retrieval, and must be inferred using aerosol loading-dependent observations and location information. In contrast, HSRL-1 makes direct measurements of aerosol intensive properties, including the lidar ratio, that provide information on aerosol type. In this study, comparisons are made for 109 underflights of the CALIOP orbit track. We find that 62% of the CALIOP marine layers and 54% of the polluted continental layers agree with HSRL-1 classification results. In addition, 80% of the CALIOP desert dust layers are classified as either dust or dusty mix by HSRL-1. However, agreement is less for CALIOP smoke (13%) and polluted dust (35%) layers. Specific case studies are examined, giving insight into the performance of the CALIOP aerosol type algorithm. In particular, we find that the CALIOP polluted dust type is overused due to an attenuation-related depolarization bias. Furthermore, the polluted dust type frequently includes mixtures of dust plus marine aerosol. Finally, we find that CALIOP's identification of internal boundaries between different aerosol types in contact with each other frequently do not reflect the actual transitions between aerosol types accurately. Based on these findings, we give recommendations which may help to improve the CALIOP aerosol type algorithms.


2005 ◽  
Vol 277-279 ◽  
pp. 816-823
Author(s):  
Sang Hee Lee ◽  
Gi Hyuk Choi ◽  
Hyo Suk Lim ◽  
Joo Hee Lee ◽  
Kwon Ho Lee ◽  
...  

The great fires were detected through the Moderate Resolution Imaging Spectroradiometer (MODIS) observations over Northeast Asia. The large amount of smoke produced near Lake Baikal was transported to East Asia using high Aerosol Optical Thickness (AOT) as seen through the satellite images. The smoke pollution from the Russian forest fires would sometimes reach Korea through Mongolia and eastern China. In May 2003, a number of large fires blazed through eastern Russian, producing a thick, widespread pall of smoke over much of East Asia. This study focuses on the identification of the carbon monoxide (CO) for MOPITT released from MOPITT primarily into East Asia during the Russian Fires. In the wake of the fires, the 700hPa MOPITT retrieved CO concentrations which reached up to 250ppbv. Smoke aerosol retrieval using a separation technique was also applied to the MODIS data observed in 14-22 May 2003. Large AOT, 2.0 ~ 5.0, was observed over Korea on 20 May 2003 due to the influence of the long range transport of smoke aerosol plume from the Russian Fires.


2015 ◽  
Vol 8 (10) ◽  
pp. 4083-4110 ◽  
Author(s):  
R. C. Levy ◽  
L. A. Munchak ◽  
S. Mattoo ◽  
F. Patadia ◽  
L. A. Remer ◽  
...  

Abstract. To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March–April–May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.


2018 ◽  
Vol 10 (10) ◽  
pp. 3701 ◽  
Author(s):  
Jiaping Zhang ◽  
Mingwang Cheng ◽  
Xinyu Wei ◽  
Xiaomei Gong

Marital happiness is an important symbol of social harmony and can help promote sustainable economic and social development. In recent years, the rapid rise of the divorce rate in China, a country where the divorce rate had previously been low, has attracted wide attention. However, few articles have focused on the popularization of information and communication technology's impact on China’s rising divorce rate in recent years. As a first attempt, the provincial panel data during the period 2001–2016 is applied to study quantitatively the relationship between mobile phone penetration and the divorce rate. In order to get more reliable estimation results, this paper uses two indicators to measure the divorce rate, and quantile regression is applied for further analysis. Additionally, one-year to five-year lag times of the mobile phone penetration are used as the core explanatory variables in order to analyse the lagging effect of mobile phone penetration on divorce rate. The result shows that the correlation between the mobile phone penetration and the divorce rate was statistically positive significant in China during the period 2001–2016. Furthermore, the paper also finds that mobile phone penetration had the greatest impact on divorce rate in central China, followed by eastern China, but it was not obvious in western China during this period. From a technological perspective, this paper provides some possible explanations for the rising divorce rate in China in recent years, and further enriches the relevant research on the impact of the development of information and communication technology on societal changes.


2018 ◽  
Vol 53 ◽  
pp. 04008
Author(s):  
Fumin Deng ◽  
Hui Zhu ◽  
Xuedong Liang

Regional green development can commendably abide by the theory of dissipative structure. The relative dissipative characteristics taken on by regional development are analyzed, in which the energy factors and resources factors are incorporated into the green economic development and green environment support subsystems (2GE system) in line with the definite input characteristics. A more representative indicator system is established, with positive and negative entropy indexes involved. As Brusselator model and information entropy method are employed to calculate the data of 30 China’s provinces from 2008 to 2015, the findings bespeak that green development in China lays particular stress on green economic development assuming higher environment pressure and cost. The development among various regions is getting progressively and evidently different, which is manifested as potent economic base and abundant natural resources in the Eastern China; the backward green economic development and the progress of green environment in Central China; the pursuit of green economic development at the expense of the green environment in Western China and Northeastern China.


2010 ◽  
Vol 10 (4) ◽  
pp. 1953-1967 ◽  
Author(s):  
S. Peyridieu ◽  
A. Chédin ◽  
D. Tanré ◽  
V. Capelle ◽  
C. Pierangelo ◽  
...  

Abstract. Monthly mean infrared (10 μm) dust layer aerosol optical depth (AOD) and mean altitude are simultaneously retrieved over the tropics (30° S–30° N) from almost seven years of Atmospheric Infrared Sounder (AIRS) observations covering the period January 2003 to September 2009. The method developed relies on the construction of look-up-tables computed for a large selection of atmospheric situations and follows two main steps: first, determination of the observed atmospheric thermodynamic situation and, second, determination of the dust properties. A very good agreement is found between AIRS-retrieved AODs and visible optical depths from the Moderate resolution Imaging Spectroradiometer (MODIS/Aqua) during the main (summer) dust season, in particular for three regions of the tropical North Atlantic and one region of the north-western Indian Ocean. Outside this season, differences are mostly due to the sensitivity of MODIS to aerosol species other than dust and to the more specific sensitivity of AIRS to the dust coarse mode. AIRS-retrieved dust layer mean altitudes are compared to the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP/CALIPSO) aerosol mean layer altitude for the period June 2006 to June 2009. Results for a region of the north tropical Atlantic downwind of the Sahara show a good agreement between the two products (σ≈360 m). Differences observed in the peak-to-trough seasonal amplitude, smaller from AIRS, are principally attributed to the large difference in spatial sampling of the two instruments. They also come from the intrinsic limit in sensitivity of the passive infrared sounders for low altitudes. These results demonstrate the capability of high resolution infrared sounders to measure not only dust aerosol AOD but also the mean dust layer altitude.


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