A study of aerosol pollution episode due to agriculture biomass burning in the east-central China using satellite data

Mukai, Sonoyo; Nakata, Makiko; Yasumoto, Masayoshi; Sano, Itaru; Kokhanovsky, Alexander A.

doi:10.3389/fenvs.2015.00057

Cited by 9 publications

(7 citation statements)

References 31 publications

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“…The MSOS method has been applied to other aerosol events in previous works, such as a forest fire in the Amazon 12 and a severe air pollution case in eastcentral China. 21 In these studies, the difference between the resimulation results and the MODIS measurements was within 3%. The validation of the retrieved aerosol properties around the target was examined together with the finite atmosphere treatments and discussed in the next section.…”

Section: Retrieval Of Aerosol Properties In Heavy Bba Eventsmentioning

confidence: 78%

“…In the case of an AOT higher than 1.0, there is no significant reason to consider that the bottom surface reflection apparently contributes to the satellite measurements. 21 Based on this assumption, we assessed the greatest impact of surface reflection on the satellite measurements considering the bottom surface reflection (surface albedo = 1.0), and the nadir viewing of the satellite at noon. In the case of AOT = 1, the satellite can observe about 10% of the incident solar radiation that is directly reflected by the bottom surface.…”

Section: August August Septembermentioning

confidence: 99%

“…Therefore, a simplification was made for the aerosol size distribution function. 21 As a result, the size distribution function for continental aerosols (V) can be approximately expressed in a simpler form, defined by the unique variable of the fine particle fraction (f) of the volume concentration 32 : E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 0 3 ; 1 1 6 ; 4 1…”

Section: Aerosol Modelmentioning

confidence: 99%

“…A detailed description of this procedure was presented in previous studies. 6,21 The dots in Fig. 13 denote the ADEOS-2/GLI data over the target on August 20, 2003.…”

Section: Retrieval Of Aerosol Properties In Heavy Bba Eventsmentioning

confidence: 99%

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Algorithms for the classification and characterization of aerosols: utility verification of near-UV satellite observations

Mukai

Sano

Nakata

2019

J. Appl. Rem. Sens.

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Aerosol types were characterized and classified using multispectral satellite data. The role of near-UV data in the detection of absorbing aerosols, such as biomass burning aerosols (BBA) or mineral dust particles (DUST), was examined on a global scale. An absorbing aerosol index (AAI) was proposed and defined as the ratio of the satellite-observed radiance (R) at a wavelength of 0.412 μm [R (0.412)] to that at 0.380 μm [R (0.380)] that can also detect nonabsorbing-type aerosols. Initially, the numerical AAI values were estimated for the BBAs and DUST from measurements collected by the Advanced Earth Observing Satellite-2/Global Imager (ADEOS-2/GLI). The Japanese short mission ADEOS-2 carried the GLI instrument with observation channels in the near-UV region. Not only the AAI index but also the short-wavelength infrared measurements were utilized to determine the dust detection index (DDI) defined as the ratio of R (2.210) to R (0.380) in order to discriminate BBAs from DUST. In addition, the AAI and DDI values were evaluated for the detection of clouds. The results allowed the classification criteria for DUST, BBA, other types of aerosols and clouds to be obtained. The Second-Generation Global Imager (SGLI) sensor is onboard the Japanese Global Change Observation Mission-Climate (GCOM-C) (SHIKISAI in Japanese) satellite launched on December 23, 2017. The SGLI has multiple channels (19) including near-UV and polarization sensors in the red and near-IR wavelengths. We also demonstrated the advantages of the SGLI for near-UV and polarization data for aerosol remote sensing. An understanding of aerosol types facilitated subsequent aerosol retrieval. Then, retrieval for classified aerosols was made based on the radiation simulations with multispectral radiance by GLI and polarization measurements by Polarization and Directionality of the Earth's Reflectances (POLDER)-2, respectively, mounted on the ADEOS-2 satellite. The proposed algorithms are expected to be available not only for the analysis of the SGLI data but also for other future missions. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Retrieval Of Aerosol Properties In Heavy Bba Eventsmentioning

confidence: 78%

Section: August August Septembermentioning

confidence: 99%

Section: Aerosol Modelmentioning

confidence: 99%

“…A detailed description of this procedure was presented in previous studies. 6,21 The dots in Fig. 13 denote the ADEOS-2/GLI data over the target on August 20, 2003.…”

Section: Retrieval Of Aerosol Properties In Heavy Bba Eventsmentioning

confidence: 99%

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Algorithms for the classification and characterization of aerosols: utility verification of near-UV satellite observations

Mukai

Sano

Nakata

2019

J. Appl. Rem. Sens.

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“…and has also been linked with heavy smog and haze episodes (e.g. Mukai et al, 2015;Stohl et al, 2007).…”

Section: Gas Flaringmentioning

confidence: 99%

Global anthropogenic emissions of particulate matter including black carbon

et al. 2017

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Abstract. This paper presents a comprehensive assessment of historical global anthropogenic particulate matter (PM) emissions including the consistent and harmonized calculation of mass-based size distribution (PM 1 , PM 2.5 , PM 10 ), as well as primary carbonaceous aerosols including black carbon (BC) and organic carbon (OC). The estimates were developed with the integrated assessment model GAINS, where source-and region-specific technology characteristics are explicitly included. This assessment includes a number of previously unaccounted or often misallocated emission sources, i.e. kerosene lamps, gas flaring, diesel generators, refuse burning; some of them were reported in the past for selected regions or in the context of a particular pollutant or sector but not included as part of a total estimate. Spatially, emissions were calculated for 172 source regions (as well as international shipping), presented for 25 global regions, and allocated to 0.5 • × 0.5 • longitude-latitude grids. No independent estimates of emissions from forest fires and savannah burning are provided and neither windblown dust nor unpaved roads emissions are included.We estimate that global emissions of PM have not changed significantly between 1990 and 2010, showing a strong decoupling from the global increase in energy consumption and, consequently, CO 2 emissions, but there are significantly different regional trends, with a particularly strong increase in East Asia and Africa and a strong decline in Europe, North America, and the Pacific region. This in turn resulted in important changes in the spatial pattern of PM burden, e.g. European, North American, and Pacific contributions to global emissions dropped from nearly 30 % in 1990 to well below 15 % in 2010, while Asia's contribution grew from just over 50 % to nearly two-thirds of the global total in 2010. For all PM species considered, Asian sources represented over 60 % of the global anthropogenic total, and residential combustion was the most important sector, contributing about 60 % for BC and OC, 45 % for PM 2.5 , and less than 40 % for PM 10 , where large combustion sources and industrial processes are equally important. Global anthropogenic emissions of BC were estimated at about 6.6 and 7.2 Tg in 2000 and 2010, respectively, and represent about 15 % of PM 2.5 but for some sources reach nearly 50 %, i.e. for the transport sector. Our global BC numbers are higher than previously published owing primarily to the inclusion of new sources.This PM estimate fills the gap in emission data and emission source characterization required in air quality and climate modelling studies and health impact assessments at a regional and global level, as it includes both carbonaceous and non-carbonaceous constituents of primary particulate matter emissions. The developed emission dataset has been used in several regional and global atmospheric transport and climate model simulations within the ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) project and beyo...

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Remote Sensing of Heavy Aerosol Pollution Episodes: Smoke and Dust

Mukai

2018

Remote Sensing of Aerosols, Clouds, and Precipitation

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A study of aerosol pollution episode due to agriculture biomass burning in the east-central China using satellite data

Cited by 9 publications

References 31 publications

Algorithms for the classification and characterization of aerosols: utility verification of near-UV satellite observations

Algorithms for the classification and characterization of aerosols: utility verification of near-UV satellite observations

Global anthropogenic emissions of particulate matter including black carbon

Remote Sensing of Heavy Aerosol Pollution Episodes: Smoke and Dust

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