Matches in SemOpenAlex for { <https://semopenalex.org/work/W4224920802> ?p ?o ?g. }
- W4224920802 endingPage "2058" @default.
- W4224920802 startingPage "2058" @default.
- W4224920802 abstract "Identification of aerosol types has long been a difficult problem over East and South Asia due to various limitations. In this study, we use 2-dimensional (2-D) and multi-dimensional Mahalanobis distance (MD) clustering algorithms to identify aerosol characteristics based on the data from the Aerosol Robotic Network from March 1998 to February 2018 over the South and East Asian region (10°N~50°N, 70°E~135°E). The single scattering albedo (SSA), absorption Angstrom exponent (AAE), extinction Angstrom exponent (EAE), real index of refraction (RRI), and imaginary index of refraction (IRI) are utilized for classification of aerosols. Sub-regions with similar background conditions over East and South Asia are identified by hierarchical clustering algorithm to illustrate distinctive meteorological states in different areas. The East and South Asian aerosols are found to have distinct regional and seasonal features relating to the meteorological conditions, land cover, and industrial infrastructure. It is found that the proportions of dust aerosol are the highest in spring at the SACOL site and in summer at the sites near the Northern Indo-Gangetic Plain area. In spring, biomass-burning aerosols are dominant over the central Indo-China Peninsula area. The aerosol characteristics at coastal sites are also analyzed and compared with previous results. The 2-D clustering method is useful when limited aerosol parameters are available, but the results are highly dependent on the sets of parameters used for identification. Comparatively, the MD method, which considers multiple aerosol parameters, could provide more comprehensive classification of aerosol types. It is estimated that only about 50% of the data samples that are identifiable by the MD method could be classified by the 2-D methods, and a lot of undetermined data samples could be mis-classified by the 2-D methods. The aerosol radiative forcing (ARF) and the aerosol radiative forcing efficiency (ARFE) of various aerosol types at the top and the bottom of the atmosphere (TOA and BOA) are determined based on the MD aerosol classification. The dust aerosols are found to have the largest ARF at the TOA (−36 W/m2), followed by the urban/industrial aerosols and biomass-burning aerosols. The ARFE of biomass-burning aerosols at the BOA (−165 W/m2/AOD550nm) is the strongest among those of the other aerosol types. The comparison of the results by MD and 2-D methods shows that the differences in ARF and ARFE are generally within 10%. Our results indicate the importance of aerosol type classification in accurately attributing the radiative contributions of different aerosol components." @default.
- W4224920802 created "2022-04-28" @default.
- W4224920802 creator A5034618391 @default.
- W4224920802 creator A5060529289 @default.
- W4224920802 date "2022-04-25" @default.
- W4224920802 modified "2023-10-06" @default.
- W4224920802 title "Aerosols over East and South Asia: Type Identification, Optical Properties, and Implications for Radiative Forcing" @default.
- W4224920802 cites W1146251921 @default.
- W4224920802 cites W1846776786 @default.
- W4224920802 cites W1858399415 @default.
- W4224920802 cites W1967807857 @default.
- W4224920802 cites W1986402954 @default.
- W4224920802 cites W1987971958 @default.
- W4224920802 cites W2005162015 @default.
- W4224920802 cites W2005963207 @default.
- W4224920802 cites W2026703051 @default.
- W4224920802 cites W2034144697 @default.
- W4224920802 cites W2034326114 @default.
- W4224920802 cites W2035201267 @default.
- W4224920802 cites W2036432952 @default.
- W4224920802 cites W2039164341 @default.
- W4224920802 cites W2045674863 @default.
- W4224920802 cites W2048322876 @default.
- W4224920802 cites W2054059769 @default.
- W4224920802 cites W2064193920 @default.
- W4224920802 cites W2075596712 @default.
- W4224920802 cites W2077532836 @default.
- W4224920802 cites W2080223822 @default.
- W4224920802 cites W2084676053 @default.
- W4224920802 cites W2084707451 @default.
- W4224920802 cites W2085407470 @default.
- W4224920802 cites W2098050550 @default.
- W4224920802 cites W2099076331 @default.
- W4224920802 cites W2099755566 @default.
- W4224920802 cites W2111813284 @default.
- W4224920802 cites W2121745948 @default.
- W4224920802 cites W2150078821 @default.
- W4224920802 cites W2167929905 @default.
- W4224920802 cites W2171215372 @default.
- W4224920802 cites W2173852084 @default.
- W4224920802 cites W2180975152 @default.
- W4224920802 cites W2181846895 @default.
- W4224920802 cites W2197716351 @default.
- W4224920802 cites W2313040768 @default.
- W4224920802 cites W2418673772 @default.
- W4224920802 cites W2434114072 @default.
- W4224920802 cites W2469290113 @default.
- W4224920802 cites W2519497602 @default.
- W4224920802 cites W255540518 @default.
- W4224920802 cites W2614919504 @default.
- W4224920802 cites W2769790383 @default.
- W4224920802 cites W2789287442 @default.
- W4224920802 cites W2792854494 @default.
- W4224920802 cites W2795859997 @default.
- W4224920802 cites W2805509125 @default.
- W4224920802 cites W2890206031 @default.
- W4224920802 cites W2906848991 @default.
- W4224920802 cites W2938639417 @default.
- W4224920802 cites W2969969097 @default.
- W4224920802 cites W2987090337 @default.
- W4224920802 cites W3017508063 @default.
- W4224920802 cites W3036098717 @default.
- W4224920802 cites W3046331830 @default.
- W4224920802 cites W3091926628 @default.
- W4224920802 cites W3108202265 @default.
- W4224920802 cites W3114948373 @default.
- W4224920802 cites W3174037107 @default.
- W4224920802 cites W4210672288 @default.
- W4224920802 cites W4212910896 @default.
- W4224920802 cites W436670271 @default.
- W4224920802 doi "https://doi.org/10.3390/rs14092058" @default.
- W4224920802 hasPublicationYear "2022" @default.
- W4224920802 type Work @default.
- W4224920802 citedByCount "4" @default.
- W4224920802 countsByYear W42249208022022 @default.
- W4224920802 countsByYear W42249208022023 @default.
- W4224920802 crossrefType "journal-article" @default.
- W4224920802 hasAuthorship W4224920802A5034618391 @default.
- W4224920802 hasAuthorship W4224920802A5060529289 @default.
- W4224920802 hasBestOaLocation W42249208021 @default.
- W4224920802 hasConcept C127313418 @default.
- W4224920802 hasConcept C153294291 @default.
- W4224920802 hasConcept C172461840 @default.
- W4224920802 hasConcept C205649164 @default.
- W4224920802 hasConcept C2778552899 @default.
- W4224920802 hasConcept C2779345167 @default.
- W4224920802 hasConcept C39432304 @default.
- W4224920802 hasConcept C49204034 @default.
- W4224920802 hasConcept C91586092 @default.
- W4224920802 hasConcept C99578197 @default.
- W4224920802 hasConceptScore W4224920802C127313418 @default.
- W4224920802 hasConceptScore W4224920802C153294291 @default.
- W4224920802 hasConceptScore W4224920802C172461840 @default.
- W4224920802 hasConceptScore W4224920802C205649164 @default.
- W4224920802 hasConceptScore W4224920802C2778552899 @default.
- W4224920802 hasConceptScore W4224920802C2779345167 @default.
- W4224920802 hasConceptScore W4224920802C39432304 @default.
- W4224920802 hasConceptScore W4224920802C49204034 @default.