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350 results for “particulates”
Carbon and nitrogen content and stable isotope compositions from particulate organic matter samples from lagoon, river, and open ocean sites along the Alaska Beaufort Sea coast, 2018-ongoing
Multiple water types (river, lagoon, ocean) from the North Slope of Alaska and nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Water samples are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods, and analyzed for particulate organic carbon (POC) and particulate organic nitrogen (PON) content and stable isotopic composition.
PIE LTER dissolved nutrient and particulate concentrations of freshwater inputs to the Plum Island estuarine system, Massachusetts, taken approximately monthly.
Multi-year data of water chemistry including nutrient concentrations for various forms of N, P, C, as well as suspended sediments, was determined from monthly grab samples taken at watershed inputs to the Plum Island Sound Estuary. Sampling sites were the Ipswich River (Sylvania Dam, Ipswich, MA), Parker River Dam (Central St, Newbury, MA), Egypt River (Ipswich, MA) Mill River (Newbury, MA), Muddy Run (Ipswich, MA), Little River (Newbury, MA). These nutrient concentrations are then used in conjunction with USGS discharge data (recorded at gages in the Parker River at Byfield, MA and the Ipswich River at Ipswich, MA) to calculate annual nutrient loading to the Plum Island Sound Estuary, coming over each dam. Annual yield is also calculated for both dams. Refer to file WAT-VA-Load for loading data.
Stream Suspended Sediment and Particulate Organic Matter at Harvard Forest 2009-2010
In addition to conveying water and nutrients and providing habitat to a variety of ecosystems, streams transport downstream mineral sediment and other particulate matter washed in from hillslopes and eroded from its channel and banks. At high levels, suspended sediment can be a devastating pollutant for aquatic organisms. The amount of suspended material in a stream varies tremendously with discharge; typically, suspended sediment increases with discharge, as stormwater runoff and overland flow carry particles from the hillslopes into the channel. Suspended sediment can also be a function of land use and vegetation, both of which affect the infiltration capacity of the landscape; more infiltration generally means less surface runoff and thus less sediment. Forested watersheds such as the Bigelow Brook watershed will typically have less suspended sediment than similar watersheds in urban environments. By analyzing how suspended sediment varies with discharge, I will be able to compare the relative effectiveness of overland flow of stormwater in washing materials into the streams. It is also possible that tree loss due to the wooly adelgid, ice storms, or fire in the watershed may increase the amount of sediment to Bigelow Brook, as a loss in tree canopy may result in more soil erosion due to rain splash and more water overall reaching the stream. For this reason, I hope to continue monitoring sediment in Bigelow Brook for an extended period of time to record any significant changes due to changing vegetation. Furthermore, by determining how much of the suspended sediment consists of particulate organic matter (using standard LOI techniques), I will be able to estimate the net carbon export from the two watersheds via that pathway. Preliminary, back-of-the-envelope calculations suggest that as much as 3-5% of the total annual carbon export leaves the Harvard Forest watershed via stream-transported particulate organic matter. To this end, I propose to measure suspended
North Temperate Lakes LTER: Total Particulate Matter - Madison Lakes Area 2000 - 2013
Total particulate matter is measured at one station in the deepest part of each lake at the top of the epilimnion for lakes Mendota, Monona, Fish and Wingra. Sampling Frequency: bi-weekly during ice-free season from late March or early April through early September, then every 4 weeks through late November; sampling is conducted usually once during the winter (depending on ice conditions). Number of sites: 4
PIE LTER water-column nutrient and particulate transects along the Parker River Estuary, Massachusetts, 1994 - 2019.
Water chemistry including nutrient concentrations for various forms of N, P, C, as well as suspended sediments and light extinction coefficients, was determined from bi-annual nutrient transects along the Plum Island Sound estuary from the Parker River Dam to the mouth of the sound. Grab samples were taken at 11 sites along a 24 km transect from the mouth of the estuary to as near the dam at the head of the estuary as poosible. These samples have generally been collected in Spring and Fall and are done in conjunction with metabolism transects measuring dissolved oxygen levels. The Spring and Fall transects correspond to the high-flow, pre-growth season and the low-flow, post-growth season, respectively.
Particulate organic carbon and particulate organic nitrogen concentrations and stable isotope composition of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains particulate organic carbon and particulate organic nitrogen concentrations and stable isotope composition (delta 13C and delta 15N) sampled during the Antarctic Circumnavigation Expedition (ACE) Leg 1-3. Water samples were collected from the underway seawater supply every 3 hours, filtered onto pre-combusted glass fibre filters, acidified to remove inorganic compounds and analysed for both elements on the same filter using an elemental analyser. These samples provide an estimate of the organic carbon and organic nitrogen concentration and carbon and nitrogen stable isotope composition of living and detrital particles > 0.7 micrometres in size.</p> <p><strong>Dataset contents</strong></p> <ul> <li>README.txt, metatdata, text</li> <li>data_file_header.txt, metadata, text</li> <li>ace_uw_poc_pon_blanks_20200512CURRSGCMR.csv, data file, comma-separated values</li> <li>ace_uw_poc_pon_20200512CURRSGCMR.csv, data file, comma-separated values</li> </ul>
PARAGON 1 - KM2112 - Particulate Carbon and Nitrogen Timecourse Incubations
<p>This dataset contains measurements of particulate carbon and nitrogen concentrations collected during the PARAGON 1 expedition (KM2112) in the North Pacific Subtropical Gyre. Measurements come from time-course incubation experiments initiated with whole seawater collected at 150 m using trace metal clean techniques and modified with various additions of organic carbon, iron, and/or nitrogen. Samples for measurements of particulate carbon and nitrogen concentrations were collected at multiple time points for each experimental biological replicate by filtering 4 L of seawater from polycarbonate incubation bottles onto pre-combusted 25 mm glass fiber filters (GF/F, Whatman) under positive pressure. Filters were then transferred to polystyrene Petri dishes lined with pre-combusted aluminum foil and stored at -20°C until analysis onshore. Filters were then analyzed by high temperature combustion using an Exeter CE-440 Elemental Analyzer according to Grabowski et al. (2019). Particulate carbon concentrations are measurements of total particulate carbon, including both organic and inorganic carbon. Timestamp is in UTC.</p>
PARAGON 1 - KM2112 - Particulate Carbon and Nitrogen In Situ Measurements
<p>This dataset contains measurements of particulate carbon and nitrogen concentrations collected during the PARAGON 1 expedition (KM2112) in the North Pacific Subtropical Gyre. Measurements come from daily collections of whole seawater at 150 m using trace metal clean techniques. Samples for measurements of particulate carbon and nitrogen concentrations were collected by filtering 4 L of whole seawater onto pre-combusted 25 mm glass fiber filters (GF/F, Whatman) under positive pressure. Filters were then transferred to polystyrene Petri dishes lined with pre-combusted aluminum foil and stored at -20°C until analysis onshore. Particulate carbon and nitrogen concentrations were then determined by high temperature combustion using an Exeter CE-440 Elemental Analyzer according to Grabowski et al. (2019). Particulate carbon concentrations are measurements of total particulate carbon, including both organic and inorganic carbon. Timestamp is in UTC.</p>
PARAGON 2 - KM2209 - Particulate Carbon and Nitrogen Timecourse Incubations
<p>This dataset contains measurements of particulate carbon and nitrogen concentrations collected during the PARAGON 2 expedition (KM2209) in the North Pacific Subtropical Gyre. Measurements come from time-course incubation experiments initiated with whole seawater collected at 150 m using trace metal clean techniques and modified with various additions of organic carbon, iron, and/or nitrogen. Samples for measurements of particulate carbon and nitrogen concentrations were collected at multiple time points for each experimental biological replicate by filtering 4 L of seawater from polycarbonate incubation bottles onto pre-combusted 25 mm glass fiber filters (GF/F, Whatman) under positive pressure. Filters were then transferred to polystyrene Petri dishes lined with pre-combusted aluminum foil and stored at -20°C until analysis onshore. Filters were then analyzed by high temperature combustion using an Exeter CE-440 Elemental Analyzer according to Grabowski et al. (2019). Particulate carbon concentrations are measurements of total particulate carbon, including both organic and inorganic carbon. Timestamp is in UTC.</p>
Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany
<p>The dataset consists of particulate matter pollution concentration, measured in three localities - Hermsdorf, Charlottenburg and Adlershof, in Berlin, Germany.</p> <p><a href="../api/records/10076056/draft/files/pm25_summer_rd_30s.geojson/content" target="_blank" rel="noopener noreferrer">pm25_summer_rd_30s.geojson</a> shows the observed PM2.5 concentration in a 30 second interval.</p> <p><a href="../api/records/10076056/draft/files/pm25_summer.geojson/content" target="_blank" rel="noopener noreferrer">pm25_summer.geojson</a> shows the concentrations shown is the local concentration (observed concentration - background concentration) in a 30 second interval. The background concentration is calculated as the lowest 5 percentile of the measured concentration for each measurement round. </p> <p><a href="../api/records/10076056/draft/files/PM2.5_lc_max.geojson/content" target="_blank" rel="noopener noreferrer">PM2.5_lc_max.geojson</a> contains the information from <a href="../api/records/10076056/draft/files/pm25_summer.geojson/content" target="_blank" rel="noopener noreferrer">pm25_summer.geojson</a> in a 25m resolution. Additionally, it contains the land use information for each coordinate.</p> <p>The original publication providing all necessary background information on study sites, methodology and data processing is the following: Venkatraman Jagatha, J., T. Sauter, C. Schneider (2024): Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany. MDPI Sensors, 24(13), 4193, DOI: 10.3390/s24134193. The paper is fully open access and can be downloaded at <a href="https://doi.org/10.3390/s24134193">https://doi.org/10.3390/s24134193</a>.</p> <p>Information on working with geojson file can be found under <a href="https://geojson.readthedocs.io/en/latest/">GeoJSON</a> .</p>
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>
Fine particulate matter (PM2.5) concentrations in downtown Phoenix, Arizona (USA) on August 20, 2024
This dataset contains a collection of estimated particulate matter (PM2.5) concentrations for downtown Phoenix, Arizona (USA), on a typical summer day (August 20, 2024) at three critical times of day (7 a.m., 1 p.m., and 5 p.m.). The 100-m resolution estimates were generated using a pre-trained support vector regression model. This dataset can inform public health interventions related to air quality.
Particulate organic carbon (POC) and nitrogen (PON) from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2017
Particulate organic carbon and nitrogen are measured from discrete bottle samples collected during CTD-rosette casts on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises (ongoing since 2017). Sampling frequency is approximately seasonal. Samples were filtered and collected on combusted glass fiber filters, pelletized using ultra clean tin disks, and combusted using a Flash EA1112 CHN analyzer to calculate concentrations of particulate organic carbon and particulate organic nitrogen in micromoles per liter. Values are also reported as concentrations in micrograms per liter and carbon to nitrogen molar ratio.
Vertical fluxes of particulate carbon, nitrogen and phosphorus from a sediment trap deployed west of Palmer Station, Antarctica at a depth of 170 meters, 1992-2019.
Particulate organic matter is exported from the upper ocean euphotic zone in the form of large sinking particles and as dissolved material. Particle fluxes to depth link the surface and mesopelagic realm and supply food to the benthos. Sedimentation flux is typically measured with sediment traps of various designs. Palmer LTER has deployed a time-series trap near 64.5degrees S, 66.0degrees W since late 1992. The trap is moored in 300 m depth and collects sinking particles at 150 m. Deployments and analyses were performed by David Karl, University of Hawaii until 2002 when Hugh Ducklow took over the sediment trap operations.Sedimentation at the PAL site of the West Antarctic Peninsula demonstrates extreme seasonality, with a well-defined pulse in the Austral summer following sea ice retreat. Daily sedimentation rates during the summer flux event are among the highest recorded globally. During the Austral winter when the ocean is covered by sea ice and shrouded in darkness, fluxes are among the lowest observed anywhere. Sedimentation rates at PAL typically vary by 4 orders of magnitude. There is also order of magnitude variability in the total annual flux (area under the curve).
Ionic composition of particulate matter (PM10) from high-volume sampling over the Southern Ocean during the austral summer of 2016/2017 on board the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Aerosol particles originate from a variety of sources (Tomasi and Lupi, 2017). Information on particle chemical composition can be utilized to access particle origin. During the Antarctic Circumnavigation Expedition (ACE) cruise around the Southern Ocean, off-line filter sampling of ambient air was performed. Filters were stored on the ship (at -20 degrees C) and after the cruise concluded analysed at Leibniz-Institute for Tropospheric Research (TROPOS) concerning ionic composition of sampled material. Here, we give mass concentrations for inorganic ions (chloride, sodium, potassium, magnesium, calcium, ammonium, nitrate, sulphate, and bromide), organic constituents (methane-sulfonic acid and oxalate), and total filter load of particles with a mobility diameter smaller 10 micrometers (PM10) for each 24 hour-sampled filter.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_particulate_matter_pm10_ionic_composition_highvolume.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This ionic composition of particulate matter (PM10) from high-volume sampling dataset 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>
Dataset: Effective T-matrix of a cylinder filled with a random 2D particulate
<p>This data is the one used in the paper "Effective T-matrix of a cylinder filled with a random 2D particulate", currently submitted to the Proceedings A of the Royal Society. A preprint version of this paper can be found at: https://arxiv.org/abs/2308.13338</p> <p>This dataset contains the numerically computed effective T-matrix of a cylinder filled with a random 2D particulate. Since the T-matrix is diagonal, only the diagonal elements T_n are computed. Values of T_n are provided for various set of parameters (frequency, particle type and volume fraction). Furthermore, for each set of parameters, T_n is computed with three different methods:</p> <p>1) The Monte Carlo method (MC), which requires computing the scattered field for several configurations of particles.</p> <p>2) The Effective Waves Method (EWM), based on results on random particulate materials. It provides a formula of the effective T-matrix with an effective wavenumber.</p> <p>3) A simplified version of the EWM when only monopole scattering is accounted for (EWM-MA). </p> <p>This dataset includes the following files: metadata_MC.csv and per each parameter one csv file with data records. The notations used in the headers of the files MCx.csv are described in the file header_notations.pdf.</p>
Chlorophyll a concentration, particulate organique carbon, and particle mean size index [gamma; 0.2 - 20 µm] measured using an hyperspectral spectrophotometer [ACS, Wetlabs] during the Tara Pacific Expedition 2016-2018
<p>The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples (Gorsky et al. 2019, Planes et al. 2019, Flores et al. 2020). The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide the continuous dataset originating from the hyperspectral and multispectral spectrophotometers [ACS] instruments acquiring continuously during the full course of the campaign. Surface seawater was pumped continuously through a hull inlet located 1.5 m under the waterline using a membrane pump (10 LPM; Shurflo), circulated through a vortex debubbler, a flow meter, and distributed to a number of flow-through instruments. An [ACS] spectrophotometer (WETLabs) measured hyper-spectral (4 nm resolution) attenuation and absorption in the visible and near infrared except between Panama and Tahiti where an AC-9 multispectral spectrophotometer (WETLabs) was used instead. The flow was automatically directed through a 0.2 µm filter for 10 minutes every hour before being circulated through the spectrophotometer to eliminate the impact of biofouling and instrument drift and estimate particulate absorption [ap] and attenuation [cp] (Slade et al. 2010). Chlorophyll a content was estimated from particulate absorption line height at 676 nm (Boss et al. 2001). The particulate organic carbon concentration [poc] was estimated using an empirical relation (Gardner et al. 2006) between measured [poc] and measured [cp]. An indicator for size distribution of particles between 0.2 and ~20 µm [gamma] was calculated from [cp] (Boss et al 2001). The data was processed with custom software for underway optical data (InLineAnalysis software available on GitHub). The detailed information regarding the data processing is given in the processing report attached with the data and in Lombard et al. (In prep.). These results are preliminary: no matchup with in-situ chlorophyll from HPLC or [poc] measurements were performed.</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>
MOdern River archivEs of Particulate Organic Carbon: MOREPOC
<p>Modern River Archives of Particulate Organic Carbon (MOREPOC) version 1.1 is a new, open-access, georeferenced, global database, featuring data on POC in suspended particulate matter (SPM) collected at 233 locations across 121 major river systems. This database includes 3,546 SPM data entries, among which 3,053 with POC content, 3,402 with stable carbon isotope (δ<sup>13</sup>C) values, 2,283 with radiocarbon activity (Δ<sup>14</sup>C) values, 1,936 with total nitrogen content, and 299 with aluminum-to-silicon mass ratios (Al/Si). The MOREPOC database aims at being used by the Earth System community to build comprehensive and quantitative models for the mobilization, alteration, and fate of terrestrial POC.</p> <p>The supply of particulate organic carbon (POC) associated with terrigenous solids transported to the ocean by rivers plays a significant role in the global carbon cycle. To advance our understanding of the source, transport, and fate of fluvial POC from regional to global scales, databases of riverine POC are needed, including elemental and isotope composition data from contrasted river basins in terms of geomorphology, lithology, climate, and anthropogenic pressure. MOREPOC will benefit the scientific community carrying out research on riverine POC sources, transport, and fate, furthermore, helping inform and validate Earth system models to improve the ability to model and understand the global carbon cycle. Existing environmental raster global datasets for climate, geomorphology, lithology, tectonics, hydrology, and land use, also offer promising prospects for the use of MOREPOC for identifying the controls on POC fluxes and composition, in particular using advanced statistical analysis or machine learning techniques. Moreover, MOREPOC enables a better understanding of sources, transport, and fate of fluvial POC combined with some existing ocean sediment databases. Future updates of MOREPOC should include new bulk POC parameters as well as data on molecular fractions, thermal labile fractions, or specific components such as black carbon or fossil carbon, which should, in turn, provide additional insight into the alteration of riverine POC from source to sink, an essential feature of the global carbon cycle.</p> <p><strong>Data description</strong></p> <p>The MOREPOC database consists of two parts: 1) the master metadata (MOREPOC_v1.1); 2) the summarization of references and methods (MOREPOC_v1.1_RM). A Readme is provided to better understand all parameters provided in the MOREPOC v1.1 database. </p> <p>MOREPOC_v1.1 includes one table, avaible as Excel spreadsheet (.xslx), comma-limited table (.csv), and GIS shapefile (compiled in .rar) using WGS84 coordinate system.</p> <ul> <li>MOREPOC_v1.1.xlsx</li> <li>MOREPOC_v1.1.csv</li> <li>MOREPOC_v1.1.rar (GIS shapefile)</li> </ul> <p>MOREPOC_v1.1_RM only provides one table, avaible as Excel spreadsheet (.xslx), comma-limited table (.csv).</p> <ul> <li>MOREPOC_v1.1_RM.xlsx</li> <li>MOREPOC_v1.1_RM.csv</li> </ul> <p>The database structure of MOREPOC is listed in Table.1 to understand all provided parameters, more information can be found in the companion manuscript.</p> <table> <caption><strong>Table. 1 Description of the parameters of the MOREPOC v1.1 database.</strong></caption> <tbody> <tr> <td><strong>Parameter</strong></td> <td><strong>Description</strong></td> <td><strong>MOREPOC column name</strong></td> </tr> <tr> <td>River name</td> <td>Name of the major river basin</td> <td>bas_id</td> </tr> <tr> <td>Sub river name</td> <td>Name of the sampled river/stream</td> <td>riv_id</td> </tr> <tr> <td>Country</td> <td>Name of country or places</td> <td>country</td> </tr> <tr> <td>Continent</td> <td>Name of the continent</td> <td>cont</td> </tr> <tr> <td>Sampling site/code</td> <td>Expedition sampling ID</td> <td>code</td> </tr> <tr> <td>Sampling date</td> <td>Time (month/day/year) when the SPM sample was collected</td> <td>time_m/d/y</td> </tr> <tr> <td>Latitude</td> <td>Decimal latitude using WGS 1984</td> <td>lat</td> </tr> <tr> <td>Longitude</td> <td>Decimal longitude using WGS 1984</td> <td>lon</td> </tr> <tr> <td>Sampling technique</td> <td>Method of SPM sampling</td> <td>type_spm</td> </tr> <tr> <td>Size fraction of SPM</td> <td>Reported size fractions analyzed</td> <td>fra_spm</td> </tr> <tr> <td>SPM concentration (mg/L)</td> <td>The total dry weight of SPM in mg per liter water column</td> <td>conc_spm</td> </tr> <tr> <td>POC concentration (mg/L)</td> <td>The total dry weight of POC in mg per liter water column</td> <td>conc_poc</td> </tr> <tr> <td>POC content (%)</td> <td>The total POC content of SPM in wt %</td> <td>per_poc</td> </tr> <tr> <td>POC content uncertainty (1σ)</td> <td>The analytical uncertainty for POC content (1σ)</td> <td>perc_poc_1sd</td> </tr> <tr> <td>δ<sup>13</sup>C (‰)</td> <td>δ<sup>13</sup>C values of POC (carbonate removed) in ‰</td> <td>d13C_poc</td> </tr> <tr> <td>δ<sup>13</sup>C uncertainty (1σ)</td> <td>The analytical uncertainty for δ<sup>13</sup>C of POC</td> <td>d13C_1sd</td> </tr> <tr> <td>Δ<sup>14</sup>C (‰)</td> <td>Δ<sup>14</sup>C values of POC (carbonate removed) in ‰</td> <td>D14C_poc</td> </tr> <tr> <td>Δ<sup>14</sup>C uncertainty (1σ)</td> <td>The analytical uncertainty for Δ<sup>14</sup>C of POC</td> <td>D14C_1sd</td> </tr> <tr> <td>Fraction modern (Fm)</td> <td>Fraction modern of POC</td> <td>F14C</td> </tr> <tr> <td>Radiocarbon ages (year)</td> <td>Radiocarbon ages before present (1950)</td> <td>age_14C</td> </tr> <tr> <td>TN content (%)</td> <td>The total nitrogen content of SPM in wt %</td> <td>perc_tn</td> </tr> <tr> <td>C<sub>org</sub>/N mass ratio</td> <td>Mass ratio of POC to TN in SPM</td> <td>cn_ratio</td> </tr> <tr> <td>Al/Si mass ratio</td> <td>Mass ratio of Al to Si in SPM</td> <td>alsi_ratio</td> </tr> <tr> <td>Reference</td> <td>Full list of citations of the data source</td> <td>ref</td> </tr> <tr> <td>Complete reference</td> <td>Complete information for cited references</td> <td>ref_c</td> </tr> <tr> <td>Measured parameters</td> <td>Summarization of elemental and isotopic carbon parameters measured</td> <td>para_m</td> </tr> <tr> <td>Calculated parameters</td> <td>Summarization of elemental and isotopic carbon parameters calculated</td> <td>para_c</td> </tr> <tr> <td>Filter</td> <td>Filter used to obtain SPM</td> <td>filter</td> </tr> <tr> <td>Acid</td> <td>The acid type used to remove carbonate in SPM</td> <td>acid</td> </tr> <tr> <td>Carbonate removal method</td> <td>The method used to remove carbonate in SPM</td> <td>m_acid</td> </tr> <tr> <td>Acid concentration</td> <td>The concentration of adopted acid to remove carbonate in SPM</td> <td>conc_acid</td> </tr> <tr> <td>carbonate removal temperature</td> <td>The environmental temperature for acid to remove carbonate in SPM</td> <td>temp_acid</td> </tr> <tr> <td>Carbonate removal duration</td> <td>The reaction time used for acid to remove carbonate in SPM</td> <td>time_acid</td> </tr> <tr> <td>Note</td> <td>Additional information for carbonate removal process</td> <td>note</td> </tr> </tbody> </table> <p><strong>Contributing Data</strong></p> <p>Please contact Yutian Ke at <a href="mailto:yutianke@caltech.edu">yutianke@caltech.edu</a> or <a href="mailto:yutian.ke@universite-paris-saclay.fr">yutian.ke@universite-paris-saclay.fr</a> if you are interested in contributing your published or unpublished data to MOREPOC.</p> <p><strong>Citation</strong></p> <p>Ke, Y. T., Calmels, D., Bouchez, J., Cécile, Q.: MOdern River archivEs of Particulate Organic Carbon: MOREPOC, Dataset version 1.1, Zenodo [dataset], <a href="https://doi.org/10.5281/zenodo.6541925">https://doi.org/10.5281/zenodo.7055970</a>.</p>
Particulate organic carbon (POC) concentration in meltwater runoff of Leverett Glacier, Russell Glacier, and Isunnguata Sermia, southwest Greenland (2009-2018)
<p>This dataset describes particulate organic carbon (POC) and particulate carbon (PC) concentrations of suspended sediments in the proglacial rivers of 3 land-terminating glaciers in the Kangerlussuaq area, Southwest Greenland: Leverett Glacier (LG), Leverett River; Russell Glacier (RG), Akuliarusiarsuup Kuua; and Isunnguata Sermia (IS), Isortoq River. Both the Leverett River and Akuliarusiarsuup Kuua are tributaries of the Qinnguata Kuussua (also known as Watson River). The data have already been part of 3 different publications (Lawson et al. 2014, Kohler et al. 2017, and Vrbická et al. 2022) but are archived here for the first time.</p> <p>POC data was collected for LG during the 2009 and 2010 melt seasons (Lawson et al. 2014) as well as 2015 (Kohler et al. 2017). For the 2018 melt season, only total carbon concentrations of suspended sediments (PC) is archived as opposed to POC (see Vrbická et al. 2022).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.