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159 results for “O3”
LESO-CN&EU&US-O3-DAILY/MONTHLY/YEARLY
<p>Hourly to yearly surface ozone (O3) concentration in China (mainland), Europe, and the United States on a 0.1 deg scale. The date range is from 2012 to 2021. This is the product of the LESO framework. The algorithm publications are 'Learning Surface Ozone From Satellite Columns (LESO): A Regional Daily Estimation Framework for Surface Ozone Monitoring in China' and 'Satellite-derived estimates of surface ozone by LESO: Extended application and performance evaluation'.</p>
VOCdata_O3_Na2S2O3scrubber
<ul> <li>contact: Lisa Ernle (lisa.ernle@mpic.de), M. Akima Ringsdorf (a.ringsdorf@mpic.de), Jonathan Williams (jonathan.williams@mpic.de)</li> <li>instruments: fast GC-MS SOFIA (MPIC), PTR-ToF-MS 4000 (Ionicon)</li> <li>merged dataset</li> <li>calibrated with VOC standard gas mix (Apel-Riemer Environmental Inc., Colorado, USA)</li> <li>all values are parts per billion (ppb)</li> <li>for information concerning updated versions, please see ReadMe.txt</li> </ul>
Dataset 8 of 8: Ozone (O3) concentrations in California (2016-2019) (CARB 19RD004)
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Dataset parent CARB 19RD004: Daily pollutant concentrations of NO2, PM2.5 and O3 of 100 m resolution for California 2012-2019
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Modelling system for computing the tropospheric O3 and CH4 perturbations from South Korean Emissions (KORUS-AQ period)
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Dataset 7 of 8: Ozone (O3) concentrations in California (2012-2015) (CARB 19RD004)
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Realistic LIGO/Virgo/KAGRA observing scenarios based on O3 public alerts
<p>Efforts to search for electromagnetic counterparts of gravitational-wave sources have intensified dramatically since the 2017 discovery a binary neutron star merger with an associated gamma-ray burst, optical/infrared kilonova, and panchromatic afterglow. Now, one LIGO/Virgo observing run later, there has not yet been a second secure identification of electromagnetic counterpart. This is not unexpected, and can be mostly explained by the localization uncertainty of events from LIGO and Virgo’s most recent, third observing run (“O3”). The official LIGO/Virgo observing scenarios fail to account for improvements in data analysis that allow LIGO/Virgo to detect fainter and hence worse-localized gravitational- wave sources, which increases the number of detections while decreasing the proportion of well-localized “gold-plated” events. Realistic forecasting of gravitational-wave localization performance is paramount because electromagnetic counterpart searches require large commitments of telescope time. We present simulations of the next several LIGO/Virgo/KAGRA observing runs that are based on the statistics of O3 public alerts.</p>
CAMSRA_Surface_O3
<p>This data is downloaded from CDS and it is produced by ECMWF with the name of CAMS global reanalysis (EAC4).</p> <p>Generated using Copernicus Climate Change Service information 2021</p> <p>Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.</p>
CAMSRA_Surface_O3_O3S_NA
<p>This data is downloaded from CDS and it is produced by ECMWF with the name of CAMS global reanalysis (EAC4).</p> <p>Generated using Copernicus Climate Change Service information 2021</p> <p>Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.</p> <p>These are 3hourly surface O3 and O3S data from 2003 to 2020 and have only the data in the North America region ([-150,-60,0,60]).</p>
AirGAM 2022r1 O3 results for all stations 2005-2019
<p>Contains all trend, cross-validation and evaluation results for O3.</p>
Elevated O3 inhibited isoprene emission of a diploid and a triploid genotype of Populus tomentosa by different mechanisms
<p>Ozone (O<sub>3</sub>) pollution affects plant growth and isoprene (ISO) emission. However, the response mechanism of isoprene emission rate (ISO<sub>rate</sub>) to elevated O<sub>3</sub> (EO<sub>3</sub>) remains poorly understood. ISO<sub>rate</sub> was investigated in two genotypes (diploid and triploid) of Chinese white poplar (<em>Populus tomentosa</em> Carr.) exposed to EO<sub>3</sub> in an open top chamber (OTC) system. The triploid genotype had higher photosynthesis rate (A) and stomatal conductance (g<sub>s</sub>) than the diploid one. EO<sub>3</sub> significantly decreased A, g<sub>s</sub>, and ISO<sub>rate</sub> of middle and lower leaf positions in both genotypes. In the diploid genotype, the reduction of ISO<sub>rate</sub> was caused by a systematic decrease related to ISO synthesis capacity, as indicated by decreased contents of isoprene precursor dimethylallyl diphosphate (DMADP) and isoprene synthase (ISPS) protein and activity of ISPS. On the other hand, the negative effect of O<sub>3</sub> on ISO<sub>rate</sub> of the triploid genotype did not result from inhibited ISO synthesis capacity, but from increased ISO oxidative loss within the leaf. Our findings will be useful for breeding poplar genotypes with high-yield and lower ISO<sub>rate</sub>, depending on local atmospheric VOC/NO<sub>x</sub> ratio, to cope with both the rising O<sub>3</sub> concentrations and increasing biomass demand. They can also enlighten the incorporation of O<sub>3</sub> effects into process-based models of isoprene emission.</p>
KORUS-AQ gridded O3, NOx, and CO observations created using ground station data
<p>We present gridded surface air quality datasets over South Korea for three key species – ozone (O<sub>3</sub>), carbon monoxide (CO), and nitrogen oxides (NO<sub>x</sub>) during the timeframe of the Korea–US Air Quality (KORUS–AQ) mission (May–June 2016). The tenth degree hourly averaged abundances are constructed from the 300+ air quality network sites using inverse distance weighting with simple declustering. Cross–comparing the interpolated fields against the site data that was used to create them reveals high prediction skill for O<sub>3</sub> (80%) throughout South Korea, and moderate skill (60%) for CO and NOx on average in densely observed regions after individual mean bias corrections. The gridded O<sub>3</sub> and CO interpolations predict the NASA DC–8 observations in the planetary boundary layer (PBL) with high skill (80%) in the Seoul Metropolitan Area (SMA) after subtracting the mean bias. DC–8 NOx observations were much less predictable on account of consistently negative vertical gradients within the PBL. Our gridded products capture the mean and variability of O<sub>3</sub> throughout South Korea, and of CO and surface NO<sub>x</sub> in most site–dense urban centres (SMA, Cheongju, Gwangju, Daegu, Changwon, and Busan).</p>
Langley Mobile Ozone Lidar observation of the O3 and aerosol variability during the 2024/04/08 solar eclipse
<p>This dataset corresponds to the observation of the O3 at Nasa Langley Research Center in Hampton, Virginia, during the Solar eclipse of 2023/04/08.</p> <p>This dataset contains, in addition to the O3 that can be found at https://tolnet.larc.nasa.gov, the aerosols backscattering and the aerosols boundary layer (which is presented in form of black mark in the accompanying image)</p>
O1, O2, and O3 DINGO ASD Datasets
<p>ASD datasets used for training DINGO. These have been accumulated through several studies and we will be adding to this data repository as we generate more ASD datasets. For now, we are not releasing ASD datasets from O4 as this contains private LVK data. </p> <p>There are three folders corresponding to the three different observing runs. Under each observing run folder there is a subfolder (either 8s or 16s) which sets the frequency spacing for the ASD dataset. In the O3 folder, there are both 8s and 16s ASD datasets. For now, we have not generated 16s ASD datasets for O1 and O2.</p> <p>The ASD datasets come in pairs labeled asds_OBSERVING_RUN_fiducial.hdf5 and asds_OBSERVING_RUN.hdf5 respectively. The _fiducial corresponds to the fact that this asd dataset only contains one ASD which used during the first stage of training. The file without the _fiducial tag indicates that ASDs sampled from across the entire observing run are used.</p> <p>Detailed dataset generation settings for each dataset can be found by running `dingo_ls /path/to/asd_dataset.hdf5` after installing DINGO. </p>
Prescribed Burn Related Increases of Population Exposure to PM2.5 and O3 Pollution in the Southeastern US over 2013–2020
<p>Daily prescribed burn PM2.5 and MDA8-O3</p>
Full-coverage 1 km daily ambient PM2.5 and O3 concentrations of China in 2005-2017 based on multi-variable random forest model
<p>The aim of our study was to construct random forest models with high-performance, and estimate daily average PM<sub>2.5</sub> concentration and O<sub>3</sub> daily maximum 8h average concentration (O<sub>3</sub>-8hmax) of China in 2005-2017 at a spatial resolution of 1km×1km. The model variables included meteorological variables, satellite data, chemical transport model output, geographic variables and socioeconomic variables. Random forest model based on ten-fold cross validation was established, and spatial and temporal validations were performed to evaluate the model performance. According to our sample-based division method, the daily, monthly and yearly simulations of PM<sub>2.5</sub> gave average model fitting R<sup>2</sup> values of 0.85, 0.88 and 0.90, respectively; these R<sup>2</sup> values were 0.77, 0.77, and 0.69 for O<sub>3</sub>-8hmax, respectively. The meteorological variables and their lagged values can significantly affect both PM<sub>2.5</sub> and O<sub>3</sub>-8hmax simulations. During 2005-2017, PM<sub>2.5</sub> exhibited an overall downward trend, while ambient O<sub>3</sub> experienced an upward trend. Whilst the spatial patterns of PM<sub>2.5</sub> and O<sub>3</sub>-8hmax barely changed between 2005 and 2017, the temporal trend had spatial characteristic.</p> <p>Each dataset is the annual mean concentration of PM<sub>2.5</sub> or O<sub>3</sub>-8hmax based on the standard grid (Grid.csv) for that year. The coordinate system of the grid is WGS-84.</p>
Surface hourly measurement data of O3, NO2 and PM2.5 for "Large modeling uncertainty in projecting decadal surface ozone changes over urban and industrial regions of China"
<p>Surface hourly measurement data of O3, NO2 and PM2.5 during summer of 2017.</p> <p>In the .csv files, the first column contains the ID for each measurement site. "lon", "lat" are longitude and latitude, respectively.</p> <p>Date format is "YYYYMMDD_hour".</p>
Reconstructed daily ground-level MDA8 O3 over 2005-2022 in China
<p>This daily ground-level MDA8 O3 dataset covers a long time period (2005-2022) with 0.1°×0.1° gap-free grids. Here we upload the monthly and annual mean datasets. </p>
Wheel Wreck - possible windlass (WW O3)
Complex iron object (WW O3) thought to be a deck windlass from the [vessel](https://vdt.cismas.org.uk/trails/the-wheel-wreck/remains-of-the-vessel/). Source: Objaverse 1.0 / Sketchfab
Validation of the O3 Regional Somatic Tissue Oxygenation Monitor
ClinicalTrials.gov study NCT04584788. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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OpenNeuro
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