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5 results for “coarse mode aerosol”
Coarse mode aerosol particle size distribution collected in the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate to be contacted if the data is used for any purpose.</p> <p>We measured coarse mode aerosol particle size distributions with an aerodynamic particle sizer (APS, model TSI 3321) at a time resolution of five minutes during the Antarctic Circumnavigation Expedition (ACE). The diameter range is 0.7 to 19 µm. Particles in this size range are indicative of primary sea spray aerosol, biological particles and potentially long-range transported mineral dust. These particles are also important for cloud formation as they act as cloud condensation nuclei or ice nucleating particles, the latter especially in the case of biological particles and mineral dust.</p> <p>Typically the instrument reports data starting from particles with a diameter greater than 500 nm, however, particle number concentrations in the channels below 723 nm were overestimated, which is a common artefact with this instrument.</p> <p>The data have been cleaned from the influence of the exhaust of the research vessel. Temporal coverage is from December 20, 2016 to April 10, 2017. We give five-minute averaged data as dN/dlog(dp), where dN is the particle number concentration per measured size bin normalized over the logarithm of the bin width. The bin width is defined as the distance between two diameters. They are spaced equally in log-space with dlog(dp) = log(d_n+1/d_n) = 1/32. To derive the total particle number concentration one has to integrate over the diameter range taking into account the normalization by dlog(dp).</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_coarse_mode_aerosol_particle_size_distribution.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.md, metadata, text</li> </ul> <p>NaN values in a complete row denote missing values because of e.g., ship exhaust contamination, maintenance, instrument failure. NaN values which appear individually or only in small groups reflect that data were below detection limit. For latitude and longitude, NaN values are noted in cases where position data was not available for the given time period.</p> <p><strong>Dataset license</strong></p> <p>This coarse mode aerosol particle size distribution dataset collected during ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
A Pan-European, Quantile Machine learning (QML) based, Total, Fine-Mode and Coarse-Mode Aerosol Optical Depth dataset (QML AOD))
<p>The V 1.1.0 product is an improved Aerosol Optical Depth (AOD) product based on Gap-filled MAIAC AOD, which provide first full-coverage, high-resolution monitoring of fine-mode and coarse-mode aerosols in Europe from 2003-20. This dataset has successfully rectified the previously identified issue of weak associations between satellite AOD and PM2.5 in Europe, which was primarily attributable to current limitations of AOD data. Our innovative approach has yielded stronger correlations with PM10, PM2.5, and PMcoarse than previous AOD product, laying a critical groundwork for improving PM10, PM2.5, and PMcoarse predictions in further epidemiological studies or environmental monitoring.</p> <p>We have uploaded three QML AOD datasets in Geotiff format, covering the region from -27° to 72° latitude and from -25° to 45° longitude. These datasets will be useful for researchers and policymakers to better understand the impacts of aerosols on the environment and human health.</p> <p> Note: v1.0.0 product do not include MAIAC AOD in their models.</p> <p>Please read more details in our paper </p> <h1><span>Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments</span></h1> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scitotenv.2024.170593" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.scitotenv.2024.170593</span></a></p>
Datasets for: AERO-MAP: A data compilation and modelling approach to understand the fine and coarse mode aerosol composition
<p>This repository contains the data compilation, gridded datasets, model output, model source code changes and model inputs for the paper: “AERO-MAP: A data compilation and modelling approach to understand the fine and coarse mode aerosol composition “.</p> <p>The only change from the December 20, 2024 version is that a new variable "Distinct" is added which indicates whether the dataset is also included in the GHOST dataset by Bowdalo et al., 2024: https://essd.copernicus.org/articles/16/4417/2024/essd-16-4417-2024.pdf. All PM2.5 and PM10 datasets from GHOST are included in this dataset, but GHOST will be regularly updated.</p> <p> </p> <p>There are two subdirectories as tar files:</p> <p>collectoutputfiles.zip: which contains the detailed data descriptions in a csv files, gridded data in netcdf and model output in netcdf format. More details in the README file in that zipped directory.</p> <p>modelfiles.zip: which contains the Source code changes and input files needed to reproduce the simulations in the paper. More details in the README file in that zipped directory.</p>
Global coarse and fine mode aerosol optical depth (cAOD, fAOD) from 2001 to 2020
<p>Coarse and fine mode aerosol optical depth (cAOD, fAOD) is critical for understanding the impact of different particle sizes on climate. Currently, the limited data length and high uncertainty of satellite products impair the applicability of cAOD and fAOD for climate research. Here, we propose a spatio-temporal co-action deep learning model (SCAM) for the retrieval of global land cAOD and fAOD (500 nm) from 2001 to 2020, at daily temporal resolution and 1° spatial resolution.</p> <p>The cAOD and fAOD products are uploaded as Geotiff format, stretched from -89.5° to 89.5° latitude and from -179.5° to 179.5° longitude. In some certain days the products might be inavailable, due to the missing MODIS satellite data used for calculating cAOD and fAOD. </p> <p> </p>
Global daily 0.5 deg coarse mode aerosol optical depth (cAOD) from 2001 to 2021
<p>Coarse mode aerosol optical depth (cAOD) is critical for understanding the impact of coarse mode particles on climate, such as dust. Currently, the limited data length and high uncertainty of satellite products impair the applicability of cAOD for climate research. Here, we propose a spatiotemporal co-action deep learning model (SCAM) for the retrieval of global land cAOD (500 nm) from 2001 to 2021 at daily temporal resolution and 0.5° spatial resolution.</p> <p>The cAOD products are uploaded in Geotiff format, stretched from -89.5° to 89.5° latitude and from -179.5° to 179.5° longitude. On certain days the products might be unavailable, due to the missing MODIS satellite data used for calculating cAOD. </p>
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