Dataset Information

Harmonized and high-quality datasets of aerosol optical depth at a US continental site, 1997-2018.

ABSTRACT: Aerosol optical depth (AOD) characterizes the aerosol burden in the atmosphere, while its wavelength dependence is a sign of particle size. Long-term records of wavelength-resolved AOD with high quality and suitable continuity are required for climate change assessment. Typically, climate-related studies use AOD products provided by several, and perhaps different, ground-based instruments. The measurements from these instruments often have different accuracy and temporal resolution. To preserve the advantages of these products (high quality) and to reduce their disadvantages (patchy records), we generate a merged dataset obtained from four instruments deployed at a US continental site in which a nearly-continuous AOD record is found at two wavelengths (500 and 870 nm) with high quality and high temporal resolution (1-min) for a 21-yr period (1997-2018). The combined dataset addresses: (1) varying data quality and resolution mismatch of the individual AOD records, and (2) the uncertainty of the merged AOD and its relevance for user-specified needs. The generated dataset will be beneficial for a wide range of applications including aerosol-radiation interactions.

SUBMITTER: Kassianov E

PROVIDER: S-EPMC7952417 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Harmonized and high-quality datasets of aerosol optical depth at a US continental site, 1997-2018.

Kassianov Evgueni E Cromwell Erol E Monroe Justin J Riihimaki Laura D LD Flynn Connor C Barnard Jaime J Michalsky Joseph J JJ Hodges Gary G Shi Yan Y Comstock Jennifer M JM

Scientific data 20210311 1

Aerosol optical depth (AOD) characterizes the aerosol burden in the atmosphere, while its wavelength dependence is a sign of particle size. Long-term records of wavelength-resolved AOD with high quality and suitable continuity are required for climate change assessment. Typically, climate-related studies use AOD products provided by several, and perhaps different, ground-based instruments. The measurements from these instruments often have different accuracy and temporal resolution. To preserve ...[more]

PMID: 33707444

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Project description:Satellite-based PM(2.5) monitoring has the potential to complement ground PM(2.5) monitoring networks, especially for regions with sparsely distributed monitors. Satellite remote sensing provides data on aerosol optical depth (AOD), which reflects particle abundance in the atmospheric column. Thus AOD has been used in statistical models to predict ground-level PM(2.5) concentrations. However, previous studies have shown that AOD may not be a strong predictor of PM(2.5) ground levels. Another shortcoming of remote sensing is the large number of non-retrieval days (i.e., days without satellite data available) due to clouds and snow- and ice-cover. In this paper we propose statistical approaches to overcome these two shortcomings, thereby making satellite imagery a viable method to estimate PM(2.5) concentrations. First, we render AOD a robust predictor of PM(2.5) mass concentration by introducing an AOD daily calibration approach through the use of mixed effects model. Second, we develop models that combine AOD and ground monitoring data to predict PM(2.5) concentrations during non-retrieval days. A key feature of this approach is that we develop these prediction models separately for groups of days defined by the observed amount of spatial heterogeneity in concentrations across the study region. Subsequently, these methodologies were applied to examine the spatial and temporal patterns of daily PM(2.5) concentrations for both retrieval days (i.e., days with satellite data available) and non-retrieval days in the New England region of the United States during the period 2000-2008. Overall, for the years 2000-2008, our statistical models predicted surface PM(2.5) concentrations with reasonably high R(2) (0.83) and low percent mean relative error (3.5%). Also the spatial distribution of the estimated PM(2.5) levels in the study domain clearly exhibited densely populated and high traffic areas. The method we have developed demonstrates that remote sensing can have a tremendous impact on the fields of environmental monitoring and human exposure assessment.

Dataset Information

Harmonized and high-quality datasets of aerosol optical depth at a US continental site, 1997-2018.

Publications

Harmonized and high-quality datasets of aerosol optical depth at a US continental site, 1997-2018.

Similar Datasets

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