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Dataset results
22 results for “chemical monitoring”
Non-refractory particulate sulfate and chloride data from a time of flight aerosol chemical speciation monitor around the Southern Ocean in the austral summer of 2016/17, during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>The Antarctic Circumnavigation Expedition (ACE) campaign was conducted between 20th December 2016 and 19th March 2017. The time of flight aerosol chemical speciation monitor (ToF-ACSM, Aerodyne Research Inc.) was deployed. It is capable of providing 10-minute resolution chemical compositions of NR-PM1 (non-refractory particulate matter with aerodynamic diameter smaller than 1 µm), including sulphate, nitrate, ammonium and organics. Chloride is refractory and can only be measured qualitatively, that is relative changes in intensity are trustworthy while absolute concentrations are a clear underestimation, because most of the chloride is in refractory form as part of sea salt in the marine environment. Since this ACSM dataset was collected on the ship, the ship exhaust will occasionally interfere with the natural signal. Therefore data gaps exist. The overall concentrations of particulate organics, nitrate and ammonium remained low, mostly below detection limit, except during the polluted periods. Thus, we do not report these three components. Only sulphate can be retrieved as a quantitative variable from this dataset.</p> <p>This dataset provides limited information on the chemical composition of sub-micron non-refractory aerosol in the Southern Ocean and gives hints on potential sources. Chloride clearly reflects the contribution of sea salt to the aerosol population. This can be checked by relating the particulate chloride to wind speed (Landwehr et al., 2019; 10.5281/zenodo.3379590) and particles with large diameters (Schmale et al., 2019; 10.5281/zenodo.2636709). Particulate sulphate may originate from a variety of sources: sea salt (minor contribution), anthropogenic emissions and natural marine emissions of dimethylsulfide, which is converted to SO2 and sulphuric acid in the atmosphere and can subsequently partition into the particle phase via gas-phase or aqueous phase reactions (Schmale et al., 2019).</p> <p><strong>Dataset contents</strong></p> <ul> <li>raw_chl_SO4_mz_55_57_manual_with_flags.csv, data file, comma-separated values</li> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>calibration_info.csv, metadata, comma-separated values</li> </ul>
Spectral and Chemical Dataset for Ripeness Monitoring in cv. Tempranillo Grapes Using a Multispectral Sensor
<p><strong><span>The dataset consists of 1010 samples of Tempranillo grape berries, offering a comprehensive record of spectral and chemical measurements that serve as a valuable resource for evaluating berry ripeness and sugar content (ºBrix). Each row in the dataset corresponds to a single berry, and the columns include a unique identifier (ID), the date of sampling (spanning 21 different days during the ripening period in 2024), expressed as Day of the Year (DOY) from DOY 210 to DOY 284. The dataset also includes measurements for nine spectral bands which represent the reflectance values recorded by the sensor (F1–F8 and NIR), a dedicated channel to detect ambient light flicker (CLEAR), and the sugar content (</span><span>°Bx</span><span>), ranging from 4.8 to 45 </span><span>°Bx</span><span>, encompassing all maturity stages from early ripeness to over-ripeness. The dataset is structured so that rows correspond to individual berries, and columns represent the measured variables, enabling statistical and machine learning analyses</span></strong></p> <p><strong><span>Center wavelength (λp) (F1: 415 nm, F2: 445 nm, F3: 480nm, F4: 515nm, F5: 555nm, F6: 590nm, F7: 630nm, F8: 680nm)</span></strong></p>
Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors: V4.NA.02.MAPLE
<p>We estimate ground-level fine particulate matter (PM<sub>2.5</sub>) total and compositional mass concentrations over North America by combining Aerosol Optical Depth (AOD) retrievals from the NASA MODIS, MISR, and SeaWIFS instruments with the GEOS-Chem chemical transport model, and subsequently calibrated to regional ground-based observations of both total and compositional mass using Geographically Weighted Regression (GWR) as detailed in the provided reference for V4.NA.02. V4.NA.02.MAPLE further modified the V4.NA.02 GWR method with additional developments as part of the MAPLE (Mortality–Air Pollution Associations in Low-Exposure Environments) project. This adjustment was of particular value over low concentrations. The GWR method of individual components remains unchanged from V4.NA.02, but are provided are percentages to ensure mass closure and recommended to be applied to the V4.NA.02.MAPLE total PM<sub>2.5</sub>.</p> <p>Annual datasets are provided in NetCDF [.nc]. Gridded files use the WGS84 projection. Compositional estimates are provided for sulfate (SO4), nitrate (NO3), ammonium (NH4), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS). Percentages are denoted with a ‘p’ after component identifiers within filenames. A slight change in file name has been included for 2017, corresponding to minor internal changes compared to earlier years. Overall, however, the dataset is consistent throughout its entire time period and can be appropriately used for trend analysis.</p> <p><strong>Reference:</strong><br> van Donkelaar, A., R. V. Martin, et al. (2019). <strong>Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors.</strong> Environmental Science & Technology, 2019, doi:10.1021/acs.est.8b06392.</p>
Titration_DB: NMR-monitored protein pH titration chemical shift data.
<p>This archive contains a backup of the NMR titration_db database raw chemical shift data.<br> Reference: D. Farrell et al., “Titration_DB: Storage and analysis of NMR-monitored protein pH titration curves.,” Proteins, vol. 78, no. 4, pp. 843–857, 2009.</p> <p>This data was formerly hosted on an interactive website which is no longer active. The files are stored as csv format, one per protein. They are also split into three folders according to the nuclei whose chemical shifts were used to detect the measurement (1H,13C or 15 N). Much of this data was obtained from literature. A table in the zip file (titration_dataset_info.csv) associates the protein name with the original paper. </p> <p>Note that the database stored the pka values fit using a model to each residue dataset. This is not stored here.</p> <p>Also present is a file titdb.fs. This is a binary file that can only be opened using the PEATDB software. PEATDB (Protein Engineering Analysis Tool - Database) was an application for sharing, analysing and storing experimental and theoretical data from Protein Engineering experiments.<br> This is now legacy software and no longer maintained. It was used to allow interactive fitting of the titration data using the Ekin module.<br> It is still possible to install this software if you really need to. It is stored on github at https://github.com/dmnfarrell/peat.</p> <p>D. Farrell May 2019</p>
One year of high frequency monitoring of groundwater physico-chemical parameters in the Weierbach Experimental Catchment, Luxembourg.
<p><span>We present a novel dataset from the Weierbach Experimental Catchment in Luxembourg, derived from a year-long high-frequency monitoring campaign focused on groundwater physico-chemical parameters. Through meticulous data collection and rigorous quality control, parameters such as electrical conductivity, dissolved oxygen, oxidation-reduction potential, pH and cations/anion concentrations were measured, offering new insights into the CZ's hydrological and biogeochemical dynamics. The dataset highlights the intricate interplay between redox reactions, pH, and ion exchange processes, as well as the influence of seasonal variability and flowline interactions on solute transport.</span></p> <p><span>By providing a detailed view of the catchment's response to hydrological changes, this dataset fills a significant gap in CZ research, offering a valuable resource for advancing our understanding of hydro-biogeochemical catchment processes. This contribution is not only a step forward in CZ science but also serves as a critical tool for researchers and practitioners aiming to refine models, inform land management practices, and foster a more holistic understanding of catchment biogeochemistry.</span></p>
Geoelectrical and hydro-chemical monitoring of karst formation at the laboratory scale
<p>We propose a dataset of two Estaillades limestone core samples subjected to acid percolation at two different rates.</p> <p>We monitored:</p> <ul> <li><strong>Permeability </strong>from high-frequency pressure gradient acquisition. Facing noise, we filtered this permeability with a Savitsky-Golay filter. Then, we resampled permeability values to compare them at specific times when we performed other measurements.</li> <li><strong>pH</strong> at the inlet and outlet.</li> <li><strong>Calcium </strong>concentration at the outlet.</li> <li><strong>Porosity</strong> was initially measured with petrophysical measurements and then calculated from calcium concentration during percolation experiments. We resampled the values to compare them at specific times when we performed other measurements.</li> <li><strong>Water electrical conductivity</strong> at the inlet and outlet.</li> <li><strong>Rock sample electrical conductivity</strong>, from which we calculated the formation factor. Rock sample electrical conductivity was high-frequency acquired. We thus resampled the values to compare them at specific times when we performed other measurements.</li> </ul> <p>We also present the pore size distribution of both samples before and after the percolation experiments. The distribution comes from the mean <strong>chord lengths distribution</strong> generated from tomography imaging.</p> <p>In addition to this dataset, we display a picture of the mesh of the sample and the electrodes generated with EIDORS software and with which we computed the geometric factor.</p>
Fig 2 in Monitoring and assessing the physico-chemical water properties and planktonic communities in tilapia nursing pond
Fig 2: Percentages of different phytoplankton communities during the study period (a, b c, are indicating the size category as small, medium and large)
Fig 1 in Monitoring and assessing the physico-chemical water properties and planktonic communities in tilapia nursing pond
Fig 1: Percentages of total phytoplankton and total zooplankton in all size categorized pond during the sampling period
Long-term snow chemical composition monitoring - Hansbreen glacier (Hornsund) - raw data
<p>During the accumulation season, snow samples were taken on Hansbreen Glacier. Several times per season. Snow samples were collected in polyethylene sterile bags and transported to the Polish Polar Station Hornsund. After melting at room temperature, the pH, conductivity and chemical composition (major ions) were analysed in the chemical laboratory of the Polish Polar Station.<br> Snow chemical composition: major ions, HCO3-, pH, conductivity</p> <p>Presented data from 2015 to 2019</p> <p>The data has not been checked, which means that it is raw data.</p> <p>Principal Investigator (PI) Adam Nawrot</p>
Compilation of chemical pollution monitoring data for the water of mountain lakes
<p>Compilation of chemical pollution monitoring data for the water of mountain lakes. Includes data for wide variety of chemical pollutants and mountain lakes from all over the world. A toxic unit (TU) based approach was used to assess the mixture toxic risks of the compiled monitoring data for each respective lake.Data will be part of an review investigating the risk for mountain lakes by chemical pollution.</p>
Monitoring of the physico-chemical composition of the Seine River based on the MeSeine network
<p>In Europe, the management of freshwater ecosystem is governed by the Water Framework Directive (2000/60/CE) and its transposing legislation in France (2006-1772 of December 2006). The good ecological status of water are evaluated using a combination of several indicators such as biological and physico-chemical parameters. The Seine River crosses several important urbanized areas of France, including the Parisian conurbation (9 millions inhabitants). To ensure the good ecological status of the Seine River, the Greater Paris Conurbation Sanitation Authority (SIAAP), has constructed and operated the MeSeine network since 1990. MeSeine constitutes a tool for evaluating the quality of the Seine river and its tributaries (Marne, Oise) in terms of physico-chemistry, bacteriology, micro-contamination and faunal diversity.</p> <p>The MeSeine network extends along 125 km of the Seine River (from Choisy to Méricourt) and over 13 km along the Marne River (frome Champigny to Alfortville). It is structured around tree pillars:</p> <ul> <li>Real time monitoring of the physico-chemical composition of the Seine river using in situ sensor, in particular dissolved oxygen and temperature sensors</li> <li>Sampling and laboratory analysis campaigns to monitor watercourses quality and comply with the quality standards as defined by the Water Framework Directive (good ecological and chemical parameters)</li> <li>Biota monitoring to appreciate the diversity of fish populations, macro-invertebrates and diatoms.</li> </ul> <p>The aim of this work is to provide data on the physico-chemical quality of the Seine generated by the MeSeine observatory via the open platform Zenodo.</p>
Data for "Characterization of composition and sources of atmospheric submicron particles in Xi'an, China during summer using an aerosol chemical speciation monitor"
<p>The dataset used for the study of Li et al. (2020). </p>
Data on monitoring the formation of chemical cocktails in urban streams in response to Freshwater Salinization Syndrome
<p>Data include the concentration of base cations and nutrients over time and over space in urban streams near the University of Maryland campus in College Park, Maryland, USA. Data were collected longitudinally along streams and over 24-hour time periods. Data on the retention and release of base cations and trace elements were also collected through incubation experiments. </p>
European demonstration program on the effect-based and chemical identification and monitoring of organic pollutants in European surface waters - Supporting Material
<p>This data contains the supporting material of the publicaiton <a href="https://www.sciencedirect.com/science/article/pii/S0048969717314365">European demonstration program on the effect-based and chemical<br> identification and monitoring of organic pollutants in European surface waters.</a></p> <p> </p>
Long-term snow chemical composition monitoring - Ariebreen glacier (Hornsund) - raw data
<p>Since 2020, snow samples have been taken from the Ariebreen glacier several times a season during the accumulation season. The snow samples are collected in polyethylene sterile bags and transported to the Polish Polar Station Hornsund. After melting at room temperature, they are analysed in the chemical laboratory of the Polish Polar Station for pH, conductivity and chemical composition (major ions).<br> <br> Site Information Ariebreen - 0.5 km long glacier between Skoddefjellet and the northern part of Ariekammen, southernmost in Wedel Jarlsberg Land.</p> <p>Presented data from 2020 to 2022</p> <p>The data has not been checked, which means that it is raw data.</p> <p>Principal investigator (PI) Adam Nawrot</p>
data for "A machine-learned approach to monitor chemical reaction via in-situ infrared spectroscopy"
<p>Source spectral and structural data of the AIMD trajectory and NEB calculation</p> <p>1. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/180-structure-IR.zip">180-structure-IR</a>.zip Source spectral and structural data of the AIMD trajectory for the selected 180 configurations</p> <p>2. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/md-pos-1.xyz?versionId=1a43760b-5cba-4548-85e6-6a45252403fc">md-pos-1.xyz</a> AIMD trajectories</p> <p>3. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-0-5100.tar.gz</a> <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-5101-7500.tar.gz</a> <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/ML-0-5100.tar.gz?versionId=ed65c63f-aa96-4be4-abef-e7a5bb7bf22f">ML-7501-9500.tar.gz</a> Source spectral and structural data of the AIMD trajectory for the extracted 9500 configurations</p> <p>4. <a href="https://zenodo.org/api/files/2d59762e-fb91-4c71-be73-fc9b18275144/split-neb-75.zip?versionId=a30f0f34-3ce2-4619-abd3-62e71174069b">split-neb-75.zip</a> Source spectral and structural data of the AIMD trajectory for the CO-CO dimerization reaction</p>
Data from: Year-long monitoring of physico-chemical and biological variables provide a comparative baseline of coral reef functioning in the central Red Sea
Open the record for dataset details and reuse information.
Data on monitoring the formation of chemical cocktails in urban streams in response to Freshwater Salinization Syndrome
Open the record for dataset details and reuse information.
Carbon Monitoring System Flux for Shipping, Aviation, and Chemical Sources L4 V1 (CMSFluxMISC) at GES DISC
This dataset provides the Carbon Flux for Shipping, Aviation, and Chemical Sources.The NASA Carbon Monitoring System (CMS) is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System will use the full range of NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
Improved chloride quantification in quadrupole aerosol chemical speciation monitors (Q-ACSMs)
<p>Particulate chloride is an important component of fine particulate matter in marine air masses. Recent field studies also report elevated concentrations of gas-phase reactive chlorine species and particulate chloride related to anthropogenic activities. This work focuses on particulate chloride detection and quantification issues observed for some quadrupole aerosol chemical speciation monitors (Q-ACSM), which are designed for long-term measurement of ambient aerosol composition. The ACSM reports particle concentrations based on the difference between measurements of ambient air (sample mode) and particle-free ambient air (filter mode). For our long-term campaign in Krakow, Poland, the Q-ACSM reports apparent negative total chloride concentration for most of the campaign when analyzed with the default fragmentation table. This is the result of the difference signal from <em>m/z</em> 35 (<sup>35</sup>Cl<sup>+</sup>) being negative which dominates over the positive difference signal from <em>m/z</em> 36 (H<sup>35</sup>Cl<sup>+</sup>). Highly time-resolved experiments with NH<sub>4</sub>Cl, NaCl and KCl particles show that the signal response of <em>m/z</em> 35 is non-ideal, where the signal builds up and decreases slowly for all three salts, leading to a negative difference measurement. In contrast, the <em>m/z</em> 36 signal exhibits a near step-change response for NH<sub>4</sub>Cl during sampling and filter period, resulting in a positive difference signal. The response of <em>m/z</em> 36 for NaCl and KCl is not as prompt as for NH<sub>4</sub>Cl but still fast enough to have a positive difference signal. Furthermore, it is shown that this behavior is mostly temperature-independent. Based on these observations, this work presents an approach to correct the chloride concentration time series by adapting the standard fragmentation table coupled with a calibration of NH<sub>4</sub>Cl to obtain a relative ionization efficiency (RIE) based on the signal at <em>m/z</em> 36 (H<sup>35</sup>Cl<sup>+</sup>). This correction can be applied for measurements in environments where chloride is dominated by NH<sub>4</sub>Cl. Caution should be exercised when other chloride salts dominate the ambient aerosol.</p> <p> </p> <p>This repository contains the data corresponding to each figure presented in the published main text.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.