Retrieving nighttime aerosol optical depth using combined measurements of satellite low light channels and ground-based integrating spheres

Li, Hao; Hu, Shensen; Ma, Shuo; Tan, Zhonghui; Ai, Weihua; Yan, Wenliang

doi:10.1080/01431161.2022.2118003

Cited by 2 publications

(2 citation statements)

References 10 publications

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“…Jiang et al [24] studied the potential of using NPP/VIIRS DNB low-light channels to monitor the AOD over North China and examined the distribution of urban lights and aerosols at night. Li et al [25] acknowledged the challenges associated with the uncertainty of urban lights and proposed a method to enhance the precision of AOD retrieval. This method utilizes combined measurements of satellite low-light channel data and ground-based integrating spheres.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, even under optimal observation conditions, the instrument can cover only 50% of the monthly nighttime hours [16]. The accuracy of the nighttime AOD retrieval algorithm may be affected by the use of satellite low-light data because of the uncertainty caused by the radiant brightness of city lights and their obvious time-varying characteristics [25]. The lack of reliable nighttime aerosol data impedes the accurate assessment of nighttime aerosol climatic effects and their subsequent environmental implications.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of All-Day Aerosol Optical Depth in the Beijing–Tianjin–Hebei Region Using Ground Air Quality Data

Zhang,

Liu,

Chen

et al. 2024

Remote Sensing

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Atmospheric aerosols affect climate change, air quality, and human health. The aerosol optical depth (AOD) is a widely utilized parameter for estimating the concentration of atmospheric aerosols. Consequently, continuous AOD monitoring is crucial for environmental studies. However, a method to continuously monitor the AOD throughout the day or night remains a challenge. This study introduces a method for estimating the All-Day AOD using ground air quality and meteorological data. This method allows for the hourly estimation of the AOD throughout the day in the Beijing–Tianjin–Hebei (BTH) region and addresses the lack of high temporal resolution monitoring of the AOD during the nighttime. The results of the proposed All-Day AOD estimation method were validated against AOD measurements from Advanced Himawari Imager (AHI) and Aerosol Robotic Network (AERONET). The R2 between the estimated AOD and AHI was 0.855, with a root mean square error of 0.134. Two AERONET sites in BTH were selected for analysis. The results indicated that the absolute error between the estimated AOD and AERONET was within acceptable limits. The estimated AOD showed spatial and temporal trends comparable to those of AERONET and AHI. In addition, the hourly mean AOD was analyzed for each city in BTH. The hourly mean AOD in each city exhibits a smooth change at night. In conclusion, the proposed AOD estimation method offers valuable data for investigating the impact of aerosol radiative forcing and assessing its influence on climate change.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimation of All-Day Aerosol Optical Depth in the Beijing–Tianjin–Hebei Region Using Ground Air Quality Data

Zhang,

Liu,

Chen

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

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AOD Derivation from SDGSAT-1/GLI Dataset in Mega-City Area

Wang

et al. 2023

Remote Sensing

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Aerosol optical depth (AOD) is the key parameter for determining the aerosol radiative effects and air quality variation. It is important to quantify nighttime aerosols using satellite-based night light images to understand their diurnal variations. This study selected high-resolution low light images from the Glimmer Imager (GLI) aboard the SDGSAT-1 satellite to examine spatial–temporal changes in night light emitted from the urban surface of Beijing. The radiance observed by SDGSAT-1/GLI was used to discern the AOD changes using the radiance background method (RB) and standard deviation method (SD) based on the characterization of the radiance from artificial light sources. Cloud cleaning processes were conducted to reduce the influence of the cloud cover in the glimmer images of the derived AOD. The results showed that there are good consistencies between the derived AOD results from the remote sensing and nighttime site observations. The radiance background method is better than the standard deviation method for deriving AOD using SDGSAT-1/GLI with the RMSE of its RB (0.0984) being greater than that of the SD (0.7653). The influence of moonlight, atmospheric absorption, and positioning errors on the results is briefly discussed. This paper shows that SDGSAT-1 can obtain relatively reliable night AOD values based on our investigations using the available satellite images taken in winter and spring, and that it has the potential to provide the scientific products of nighttime AOD.

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Retrieving nighttime aerosol optical depth using combined measurements of satellite low light channels and ground-based integrating spheres

Cited by 2 publications

References 10 publications

Estimation of All-Day Aerosol Optical Depth in the Beijing–Tianjin–Hebei Region Using Ground Air Quality Data

Estimation of All-Day Aerosol Optical Depth in the Beijing–Tianjin–Hebei Region Using Ground Air Quality Data

AOD Derivation from SDGSAT-1/GLI Dataset in Mega-City Area

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