Clear-sky aerosol optical depth over East China estimated from visibility measurements and chemical transport modeling

Abstract. We determine and interpret fine particulate matter (PM2.5) concentrations in East China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean Geostationary Ocean Color Imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5/AOD ratio exhibits high consistency with ground-based measurements (MFB = −0.52–8.0 %). We evaluate the satellite-derived PM2.5 vs. the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in-situ observations in both annual averages (r = 0.81, N = 494) and monthly averages (MFB = 13.1 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical speciation of GOCI-derived PM2.5 reveals that secondary inorganics (SO42−, NO3−, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating are responsible for an increase in the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over East China for 2013 is 53.8 μg m−3, threatening the health and life expectancy of its 600 million residents.

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Estimated total emissions of trace gases from the Canberra wildfires of 2003: a new method using satellite measurements of aerosol optical depth and the MOZART chemical transport model

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-10-977-2010 ◽

2010 ◽

Vol 10 (1) ◽

pp. 977-1004

Author(s):

C. Paton-Walsh ◽

L. K. Emmons ◽

S. R. Wilson

Keyword(s):

Carbon Monoxide ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Transport Model ◽

Trace Gases ◽

Chemical Transport ◽

New Method ◽

Chemical Transport Model ◽

Additional Tool ◽

Vegetation Fires

Abstract. In this paper we describe a new method for estimating trace gas emissions from large vegetation fires using measurements of aerosol optical depth from the MODIS instruments onboard NASA's Terra and Aqua satellites, combined with the atmospheric chemical transport model MOZART. The model allows for an estimate of double counting of enhanced levels of aerosol optical depth in consecutive satellite overpasses. Using this method we infer an estimated total emission of 10±3 Tg of carbon monoxide from the Canberra fires of 2003. Emissions estimates for several other trace gases are also given. An assessment of the uncertainties in the new method is made and we show that our estimate agrees (within expected uncertainties) with estimates made using current conventional methods of multiplying together factors for the area burned, fuel load, the combustion efficiency and the emission factor for carbon monoxide. The new method for estimating emissions from large vegetation fires described in this paper has some significant uncertainties, but these are mainly quantifiable and largely independent of the uncertainties inherent in conventional techniques. Thus we conclude that the new method is a useful additional tool for characterising emissions from vegetation fires.

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Improved Estimation of Background Ozone and Emission Impacts Using Chemical Transport Modeling and Data Fusion

10.1007/978-3-662-63760-9_13 ◽

2021 ◽

pp. 89-94

Author(s):

T. Nash Skipper ◽

M. Talat Odman ◽

Yongtao Hu ◽

Petros Vasilakos ◽

Armistead G. Russell

Keyword(s):

Data Fusion ◽

Chemical Transport ◽

Transport Modeling ◽

Chemical Transport Modeling ◽

Background Ozone

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Chemical Transport Modeling: Current Approaches and Unresolved Problems

SSSA Special Publications - Chemical Mobility and Reactivity in Soil Systems ◽

10.2136/sssaspecpub11.c4 ◽

2015 ◽

pp. 49-64 ◽

Cited By ~ 2

Author(s):

William A. Jury

Keyword(s):

Chemical Transport ◽

Transport Modeling ◽

Chemical Transport Modeling

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Retrieval of the Fine-Mode Aerosol Optical Depth over East China Using a Grouped Residual Error Sorting (GRES) Method from Multi-Angle and Polarized Satellite Data

Remote Sensing ◽

10.3390/rs10111838 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1838 ◽

Cited By ~ 4

Author(s):

Yang Zhang ◽

Zhengqiang Li ◽

Zhihong Liu ◽

Juan Zhang ◽

Lili Qie ◽

...

Keyword(s):

Aerosol Optical Depth ◽

Optical Depth ◽

Residual Error ◽

East China ◽

Anthropogenic Aerosols ◽

Aerosol Model ◽

Retrieval Accuracy ◽

Aerosol Loading ◽

Fine Mode ◽

Fine Mode Aerosol

The fine-mode aerosol optical depth (AODf) is an important parameter for the environment and climate change study, which mainly represents the anthropogenic aerosols component. The Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) instrument can detect polarized signal from multi-angle observation and the polarized signal mainly comes from the radiation contribution of the fine-mode aerosols, which provides an opportunity to obtain AODf directly. However, the currently operational algorithm of Laboratoire d’Optique Atmosphérique (LOA) has a poor AODf retrieval accuracy over East China on high aerosol loading days. This study focused on solving this issue and proposed a grouped residual error sorting (GRES) method to determine the optimal aerosol model in AODf retrieval using the traditional look-up table (LUT) approach and then the AODf retrieval accuracy over East China was improved. The comparisons between the GRES retrieved and the Aerosol Robotic Network (AERONET) ground-based AODf at Beijing, Xianghe, Taihu and Hong_Kong_PolyU sites produced high correlation coefficients (r) of 0.900, 0.933, 0.957 and 0.968, respectively. The comparisons of the GRES retrieved AODf and PARASOL AODf product with those of the AERONET observations produced a mean absolute error (MAE) of 0.054 versus 0.104 on high aerosol loading days (AERONET mean AODf at 865 nm = 0.283). An application using the GRES method for total AOD (AODt) retrieval also showed a good expandability for multi-angle aerosol retrieval of this method.

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Dust Aerosol Optical Depth Retrieval over a Desert Surface Using the SEVIRI Window Channels

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2008jtecha1109.1 ◽

2009 ◽

Vol 26 (4) ◽

pp. 704-718 ◽

Cited By ~ 11

Author(s):

Bart De Paepe ◽

Steven Dewitte

Keyword(s):

Surface Temperature ◽

Aerosol Optical Depth ◽

Optical Depth ◽

Surface Radiation ◽

Retrieval Algorithm ◽

Aerosol Layer ◽

Surface Emissivity ◽

Ir Radiation ◽

Clear Sky ◽

A Minor

Abstract The authors present a new algorithm to retrieve aerosol optical depth (AOD) over a desert using the window channels centered at 8.7, 10.8, and 12.0 μm of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation satellite. The presence of dust aerosols impacts the longwave outgoing radiation, allowing the aerosols over the desert surfaces to be detected in the thermal infrared (IR) wavelengths. To retrieve the aerosol properties over land, the surface contribution to the satellite radiance measured at the top of the atmosphere has to be taken into account. The surface radiation depends on the surface temperature, which is characterized by a strong diurnal variation over the desert, and the surface emissivity, which is assumed to be constant over a time span of 24 h. The surface emissivity is based on clear-sky observations that are corrected for atmospheric absorption and emission. The clear-sky image is a composite of pixels that is characterized by the highest brightness temperature (BT) of the SEVIRI channel at 10.8 μm, and by a negative BT difference between the channels at 8.7 and 10.8 μm. Because of the lower temperatures of clouds and aerosols compared to clear-sky conditions, the authors assume that the selected pixel values are obtained for a clear-sky day. A forward model is used to simulate the thermal IR radiation transfer in the dust layer. The apparent surface radiation for the three window channels in the presence of aerosols is calculated as a function of the surface emissivity and the surface temperature, the aerosol layer temperature, and the AOD for different aerosol loadings. From these simulations two emissivity ratios, which are stored in lookup tables (LUT), are calculated. The retrieval algorithm consists of processing the clear-sky image and computing the surface emissivity, processing the instantaneous image, and computing the apparent surface radiation for the three window channels. The two emissivity ratios are computed using the radiances at 8.7 and 10.8 μm and at 8.7 and 12.0 μm, respectively. The SEVIRI AOD is obtained by the inversion of these emissivity ratios using the corresponding LUT. The algorithm is applied to a minor dust event over the Sahara between 19 and 22 June 2007. For the validation the SEVIRI AOD is compared with the AOD from the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) along the satellite track.

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