In-depth discrimination of aerosol types using multiple clustering techniques over four locations in Indo-Gangetic plains

Bibi, Humera; Alam, Khan; Bibi, Samina

doi:10.1016/j.atmosres.2016.06.017

Cited by 68 publications

(48 citation statements)

References 56 publications

(92 reference statements)

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“…A preliminary investigation of major aerosol types found over three representative major cities (Nairobi, Kampala and Dodoma) in EA is carried out via the AOD 550 versus AE 470–660 relationship, previously used by a number of authors (Kaskaoutis et al ., , ; Kumar et al ., , ; Bibi et al ., ; Yu et al ., ) over different environments. As both are spectrally dependent parameters, AE 470–660 represents the aerosol particle‐size, while AOD 550 is dependent on the aerosol column density.…”

Section: Methodsmentioning

confidence: 98%

Spatial variations and trends in AOD climatology over East Africa during 2002–2016: a comparative study using three satellite data sets

Boiyo

Kumar

Zhao

2018

Intl Journal of Climatology

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Aerosol optical depth (AOD) has become one of the most crucial parameters for climate change assessment. This study presents long‐term (2002–2016) spatio‐temporal distributions and trends in AOD over East Africa (EA) retrieved from the moderate‐resolution imaging spectroradiometer (MODIS) Aqua [Dark Target (DT) and Deep Blue (DB)] and multi‐angle imaging spectroradiometer (MISR). An inter‐comparison of AODs retrieved from different algorithms noticed significant positive correlations (r = 0.72 − 0.87) with MISR underestimating MODIS. Moderate (>0.5–0.8) to high (≥0.8) correlations in AOD exhibited over EA, with a few regions representing low (0–0.5) positive correlations. The spatial patterns of annual mean AOD were generally characterized by low (<0.2), moderate (0.2–0.35) and high (>0.35) centres over EA. The seasonal mean AODs over EA were found high (low) during the local dry (wet) seasons, with annual mean (±σ) values of 0.20 ± 0.01, 0.18 ± 0.01 and 0.20 ± 0.02 as observed by DT, DB and MISR, respectively. A single peak distribution of frequencies in AOD was observed by the three sensors in the interval 0.1–0.2, signifying a generally less polluted environment dominated by particular aerosol type. Linear trend analysis revealed an increase in AOD by 0.52, 0.57 and 0.74% year−1 as detected by MISR, DT and DB, respectively, and were consistent with those noted in key meteorological parameters. Furthermore, annual and seasonal spatial trends and tendencies revealed a general increase in AOD over EA, being positive and significant over the northern part of EA. Later, classification of major aerosol types over major cities in EA revealed dominance of continental (74.47%) followed by the mixed (16.22%) and biomass‐burning/urban‐industrial (8.02%) aerosols, with minor contributions from desert dust (1.03%) and clean maritime (0.32%) type of aerosols.

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Section: Methodsmentioning

confidence: 98%

Spatial variations and trends in AOD climatology over East Africa during 2002–2016: a comparative study using three satellite data sets

Boiyo

Kumar

Zhao

2018

Intl Journal of Climatology

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“…The list for generating these aerosols includes anthropogenic and natural sources. Natural aerosols (e.g., dust and sea salt) mostly originate from the southern dry regions and the nearby ocean [16,17], while anthropogenic aerosols originate mainly from vehicular and industrial emissions [18][19][20][21]. Dust lifted from the Thar desert, as a result of dust storms during the pre-monsoon season may be associated with increased dust concentration over the Indo-Gangetic-Plane (IGP) [22].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Trends of Aerosols over Urban Regions in Pakistan and Their Possible Links to Meteorological Parameters

et al. 2020

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Aerosol optical depth (AOD) has become one of the most crucial parameters for climate change assessment on regional and global scales. The present study investigates trends in AOD using long-term data derived from moderate resolution imaging spectro-radiometer (MODIS) over twelve regions in Pakistan. Different statistical tests are used to assess the annual and seasonal trends in AOD. Results reveal increasing AOD trends over most of the selected regions with an obvious increase over the north and northeastern parts of the study area. Annually, increasing trends (0.0002–0.0047 year−1) were observed over seven regions, with three being statistically significant. All the selected regions experience increasing AOD trends during the winter season with six being statistically significant while during the summer season seven regions experience increasing AOD trends and the remaining five exhibit the converse with two being statistically significant. The changes in the sign and magnitude of AOD trends have been attributed to prevailing meteorological conditions. The decreasing rainfall and increasing temperature trends mostly support the increasing AOD trend over the selected regions. The high/low AOD phases during the study period may be ascribed to the anomalies in mid-tropospheric relative humidity and wind fields. The summer season is generally characterized by high AOD with peak values observed over the regions located in central plains, which can be attributed to the dense population and enhanced concentration of industrial and vehicular emissions over this part of the study area. The results derived from the present study give an insight into aerosol trends and could form the basis for aerosol-induced climate change assessment over the study area.

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“…There are four sites in Beijing [53]. The program provides a long-term, continuous, and readily-accessible public database of optical, microphysical, and radiative aerosol properties for aerosol research [7,13,[54][55][56][57][58]. The products retrieved from AERONET include aerosol optical depth, Ångström exponent, aerosol size distribution, single scattering albedo (SSA), fine mode fraction (FMF), refractive indices and asymmetry factor, which use standardized instruments, calibration, processing, and distribution, verifying the accuracy of the satellite remote sensing inversion results, and are used as ground observation values by global researchers [3,14,[59][60][61].…”

Section: Aeronet Datamentioning

confidence: 99%

“…Additionally, different aerosol types originate from several sources with diverse physical and optical properties, and from various atmospheric impacts [6][7][8][9][10]. Each aerosol type has a different climatic effect due to their size and absorptive and scattering nature, such as dust particles having large sizes and sulfate aerosols having a scattering nature, whereas nitrate particles with small sizes have absorbing tendencies [7,8,[11][12][13][14][15][16]. Consequently, long-term measurements of aerosol optical properties and aerosol types at a large scale are necessary to interpret the aerosol climatic effect [17,18].…”

Section: Introductionmentioning

confidence: 99%

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

Zhao

Wang

et al. 2017

Remote Sensing

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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 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 (R 2 = 0.76 and 0.97, in Beijing and Xianghe).

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In-depth discrimination of aerosol types using multiple clustering techniques over four locations in Indo-Gangetic plains

Cited by 68 publications

References 56 publications

Spatial variations and trends in AOD climatology over East Africa during 2002–2016: a comparative study using three satellite data sets

Spatial variations and trends in AOD climatology over East Africa during 2002–2016: a comparative study using three satellite data sets

Spatiotemporal Trends of Aerosols over Urban Regions in Pakistan and Their Possible Links to Meteorological Parameters

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

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