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910 results for “pollution”
Data from: Maps made with smartphones highlight lower noise pollution during COVID-19 pandemic lockdown at four locations in Boston
<p>Noise pollution in cities has major negative effects on the health of both humans and wildlife. Using iPhones, we collected sound-level data at hundreds of locations in four areas of Boston, Massachusetts (USA) before, during, and after the fall 2020 pandemic lockdown, during which most people were required to remain at home. These spatially dispersed measurements allowed us to make detailed maps of noise pollution that are not possible when using standard fixed sound equipment. The four sites were: the Boston University campus (which sits between two highways), the Fenway/Longwood area (which includes an urban park and several hospitals), Harvard Square (home of Harvard University), and East Boston (a residential area near Logan Airport). Across all four sites, sound levels averaged 6.4 dB lower during the pandemic lockdown than after. Fewer high noise measurements occurred during lockdown as well. The resulting sound maps highlight noisy locations such as traffic intersections and quiet locations such as parks. This project demonstrates that changes in human activity can reduce noise pollution and that simple smartphone technology can be used to make highly detailed maps of noise pollution that identify sources of high sound levels potentially harmful to humans in urban environments.</p>
Data and code for publication: Advancing Maternal Transfer of Organic Pollutants across Reptiles for Conservation and Risk Assessment Purposes
<p>Dataset and r code to prepare the dataset, in support of the publication:</p> <p>"Advancing maternal transfer of organic pollutants across reptiles for conservation and risk assessment purposes"</p> <p>Munoz, C.C., Charles, S., Vermeiren, P. (2024) Environmental Science and Technology, https://doi.org/10.1021/acs.est.4c04668</p> <p>contact email: munozc.cynthia@gmail.com</p>
SUPPLEMENTARY DATA TO: Using a citizen science approach to assess nanoplastics pollution in remote high-altitude glaciers
<p>This is the repository of the supplementary data, and it contains the following files: </p> <p>Raw data files as the original output of TD-PTR-ToF-MS for all the samples, all the blanks, all the spikes and all the calibration runs (.h5 files in three zip arcives)</p> <p>Polymer library files (a zip archive including csv files.</p> <p>A data analysis file including raw data, blank subtraction and LOD correction of all measurements (xlsx file).</p> <p>A fingerprinting result file for each plastic type (xlsx file)</p> <p>A data analysis file after plastic fingerprinting (xlsx file). </p> <p> </p> <p> </p>
Outdoor air pollution impacts chronic obstructive pulmonary disease deaths in South Asia and China: a systematic review and meta-analysis
<p><strong>Background: </strong>Chronic obstructive pulmonary disease (COPD) is among leading causes of death globally. Exposure to outdoor pollution is an important cause for increased mortality and morbidity. This study presents a systemic review regarding the impact of outdoor pollution on COPD mortality in South Asia and China.</p> <p><strong>Methods: </strong>A systematic search was conducted from 1990 to June 30<sup>th</sup> 2020 in English electronic databases: PubMed, Google Scholar and CDSR (Cochrane Database of Systematic Reviews) following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following terms were used: Chronic Obstructive Pulmonary disease OR COPD OR Chronic Bronchitis OR Emphysema OR COPD Deaths OR Chronic Obstructive Lung Disease OR Airflow Obstruction OR Chronic Airflow Obstruction OR Airflow Obstruction, Chronic OR Bronchitis, Chronic AND Mortality OR Death OR Deceased AND Outdoor pollution, ambient pollution was conducted.</p> <p><strong>Results:</strong> Out of 1899 papers screened only 17 were found eligible to be included. Subjects with COPD exposed to higher levels of outdoor air pollution had a 49% higher risk of death as compared to COPD subjects exposed to lower levels of outdoor air pollution. When taking common air pollutants individually into consideration, PM10 had an odds ratio (OR) of 1.99 respectively at CI 95%, whereas SO2 had OR of 1.8 at 95% CI, and NO2 had an OR of 1.23 OR at 95% CI. These values suggest that there is an effect of outdoor pollution on COPD but not to a significant level.</p> <p><strong>Conclusion: </strong>Despite heterogeneity across selected studies, individuals exposed to outdoor pollutants were found to be at risk of COPD mortality. Though it appears to have risk, COPD mortality was not significantly associated with outdoor pollutants. Controlling air pollution can substantially decrease the risk of COPD in South Asia and China. Further researches including more prospective and longitudinal studies are urgently needed in COPD sub-groups.</p>
Pollutants found in different cemeteries around the world, according to the literature.
<p>This file contains the main articles reported in the literature, up to this date of publication (05/01/2022), of the pollutants found in cemetery regions in several different regions of the world.</p>
Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space
<p><strong>Description</strong></p> <p>This dataset contains remote sensing data from the ESA Copernicus missions Sentinel-2 and Sentinel-5P (tropsopheric NO2 column density) in the 2018-2020 timespan. The satellite measurements each cover ~3100 locations in Europe and ~100 on the US Westcoast, each with a size of 1.2x1.2km. The locations are selected such that each measurement is centered at the location of an air quality measurement station on the ground (from the European Environment Agency or the US Environmental Protection Agency, measuring NO2). This makes it possible to analyze spatiotemporally aligned remote sensing and ground-based measurements.</p> <p> The 13 Sentinel-2 bands are upsampled (bilinear) to 10m resolution and cropped to 120x120 pixel. For some locations multiple Sentinel-2 images are available. The images are stored as binary numpy `.npy` files organized into directories based on their locations. </p> <p>The Sentinel-5P data was pre-processed by mapping the measurements from consecutive satellite overpasses onto a common rectangular grid of 0.05×0.05◦(∼5×5km) across Europe. To harmonize the Sentinel-2 (10m to 60m, upscaled to 10m) and Sentinel-5P (5×3.5km, rescaled to 5×5km) imaging resolutions, the Sentinel-5P data is linearly interpolated to 10m resolution and cropped to 120×120 pixel around the locations of interest. Additionally, all measurements with a QA flag (qa_value) below 75 were discarded, following ESA recommendations. The Sentinel-5P data are stored as `.netcdf` file, organized by location. For each location, three such files are available, containing averaged Sentinel-5P measurements at different temporal frequencies (2018-2020, quarterly, monthly).</p> <p>The <p>samples_{frequency}_{area}.csv</p> files provide a list of observations with the corresponding file paths to a (cloud-free) Sentinel-2 image, the Sentinel-5P measurement, and the average NO2 concentration measurement by the EEA or EPA ground station. These files can be used for easy data-loading.</p> <p><strong>Content</strong></p> <p>The data is organized into the following files:</p> <ul> <li>README.md - this file</li> <li>sentinel-2-eea.tar.gz [33.1GB]</li> <li>sentinel-5p-eea.tar.gz [80.1GB]</li> <li>samples_2018_2020_eea.csv </li> <li>samples_quarterly_eea.csv</li> <li>samples_monthly_eea.csv</li> <li>sentinel-2-epa.tar.gz [0.15GB]</li> <li>sentinel-5p-epa.tar.gz [1.8GB]</li> <li>samples_2018_2020_epa.csv</li> <li>samples_quarterly_epa.csv</li> <li>samples_monthly_epa.csv</li> </ul> <p><strong>Acknowledgement</strong></p> <p>If you use this data set, please cite our publication:</p> <p><em>Scheibenreif, L., Mommert, M., Borth, D., "</em>Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space<em>", Tackling Climate Change with Machine Learning workshop at ICML 2021.</em></p> <p>Please refer to this publication for additional information on the data set.</p> <p>This data set contains modified Copernicus Sentinel data acquired in 2018-2020, processed by ESA.</p> <p> </p> <p><strong>Responsible Author</strong></p> <p>Linus Scheibenreif<br> University of St. Gallen, Institute of Computer Science<br> Chair Artificial Intelligence and Machine Learning<br> linus.scheibenreif ( at ) unisg.ch</p>
Pollution induces epigenetic effects that are stably transmitted across multiple generations
<p>It has been hypothesised that the effects of pollutants on phenotypes can be passed to subsequent generations through epigenetic inheritance, affecting populations long after the removal of a pollutant. But there is still little evidence that pollutants can induce persistent epigenetic effects in animals. Here we show that low doses of commonly used pollutants induce genome-wide differences in cytosine methylation in the freshwater crustacean Daphnia pulex. Uniclonal populations were either continually exposed to pollutants or switched to clean water, and methylation was compared to control populations that did not experience pollutant exposure. While some direct changes to methylation were only present in the continually exposed populations, others were present in both the continually exposed and switched to clean water treatments, suggesting that these modifications had persisted for seven months (> 15 generations). We also identified modifications which were only present in the populations that had switched to clean water, indicating a long-term legacy of pollutant exposure distinct from the persistent effects. Pollutant-induced differential methylation tended to occur at sites that were highly methylated in controls. Modifications that were observed in both continually and switched treatments were highly methylated in controls and showed reduced methylation in the treatments. On the other hand, modifications found just in the switched treatment tended to have lower levels of methylation in the controls and showed increase methylation in the switched treatment. In a second experiment we confirmed that sub-lethal doses of the same pollutants generate effects on life-histories for at least three generations following the removal of the pollutant. Our results demonstrate that even low doses of pollutants can induce transgenerational epigenetic effects that are stably transmitted over many generations. Persistent effects are likely to influence phenotypic development, which could contribute to the rapid adaptation, or extinction, of populations confronted by anthropogenic stressors.</p>
Database for the Geospatial Synthesis of Biogeochemical Attributions of Porphyrins to Oil Pollution in Marine Sediments of the Gulf of México
<p>This dataset is associated with the journal article "Geospatial Synthesis of Biogeochemical Attributions of Porphyrins to Oil Pollution in Marine Sediments of the Gulf of México" by Muñoz-Arriola and Macias-Zamora (2022). The porphyrin and biogeochemical data were obtained by and analyzed at the Universidad Autónoma de Baja California's Instituto de Investigaciones Oceanológicas. The samples were collected to identify the effects of natural and human-originated oil spills in the Campeche Sound, and these efforts are part of the oceanographic campaign Xaman-Ek.</p> <p> </p> <p>Associated references are:</p> <p>Munoz-Arriola, F. and V. Macias-Zamora (2022) <em>Geospatial Synthesis of Biogeochemical Attributions of Porphyrins to Oil Pollution in Marine Sediments of the Gulf of México</em>. Geosciences. https://doi.org/10.3390/ geosciences12020077.</p> <p>Macias-Zamora, J. V., J. A. Villaescusa-Celaya; A. Munoz-Barbosa; and G. Gold-Bouchot (1999). Trace metals in sediment cores from the Campeche shelf, Gulf of Mexico. Environmental Pollution. Vol 104:69-77.</p> <p> </p>
Characterization of legacy persistent organic pollutants (POPs) in northern bottlenose whales of the Western North-Atlantic
<p>Dataset associated with the Canadian Technical Report of Fisheries and Aquatic Sciences entitled "Characterization of legacy persistent organic pollutants (POPs) in northern bottlenose whales of the Western North-Atlantic". Presents lipid weight corrected persistent organic pollutant concentrations (microgram per gram) in the blubber of northern bottlenose whales samples in the western North Atlantic. </p>
Dataset and R code: Effects of temperature and air pollution on emergency ambulance dispatches: a time series analysis in a medium-sized city in Germany
<p>Dataset and R script to replicate results in the manuscript "Effects of temperature and air pollution on emergency ambulance dispatches: a time series analysis in a medium-sized city in Germany", currently under review.</p>
Fig. 2 in Accumulation Of Heavy Metals By Small Mammals The Background And Polluted Territories Of The Urals
Fig. 2. The dendrogram is obtained for element analysis (Cu+Zn+Cd) in small mammals from natural populations in the background zone (Bcg) and polluted territories (Imp). The results of cluster analysis confirmed the statistically significant differences in heavy metals total accumulation in three species of small mammals.
Supporting data from: Characterizing changes in eastern U.S. pollution events in a warming world
<p>Risk assessments of air pollution impacts on human health and ecosystems would ideally consider a broad set of climate and emission scenarios, as well as natural internal climate variability. We analyze initial condition chemistry-climate ensembles to gauge the significance of greenhouse-gas-induced air pollution changes relative to internal climate variability, and consider response differences in two models. To quantify the effects of climate change on the frequency and duration of summertime regional-scale pollution episodes over the Eastern United States (EUS), we apply an Empirical Orthogonal Function (EOF) analysis to a 3-member GFDL-CM3 ensemble with prognostic ozone and aerosols and a 12-member NCAR-CESM1 ensemble with prognostic aerosols under a 21st century RCP8.5 scenario with air pollutant emissions frozen in 2005. Correlations between GFDL-CM3 principal components for ozone, PM<sub>2.5</sub> and temperature represent spatiotemporal relationships discerned previously from observational analysis. Over the Northeast region, both models simulate summertime surface temperature increases of over 4 C from 2006–2025 to 2081–2100 and PM2.5 of up to 1–4 μg m<sup>−3</sup>. The ensemble average decadal incidence of upper quartile Northeast PM<sub>2.5</sub> events lasting at least three days doubles in GFDL-CM3 and increases by ∼50% in CESM1. In other EUS regions, inter-model differences in PM<sub>2.5</sub> responses to climate change cannot be explained solely by internal climate variability. Our EOF-based approach anticipates future opportunities to data-mine initial condition chemistry-climate model ensembles for probabilistic assessments of changing regional-scale pollution and heat event frequency and duration, while obviating the need to bias-correct concentration-based thresholds separately in individual models.</p>
Fuel Consumption Patterns linked to Evolution of India's PM2.5 Pollution Between 1998 and 2020
<p>These datasets are part of Supplementary information for the journal article<br> "<a href="https://doi.org/10.1039/D2EA00027J">Evolution of India’s PM2.5 Pollution Between 1998 and 2020 Using Global Reanalysis Fields Coupled with Satellite Observations and Fuel Consumption Patterns</a>"</p> <p>Pollution data summaries are listed <a href="https://doi.org/10.5281/zenodo.7115052">here</a>.<br> <a href="https://doi.org/10.5281/zenodo.7115052">https://doi.org/10.5281/zenodo.7115052</a></p> <p>Fuel consumption and activity data over the years is collected from indiastats.<br> Excel files include absolute activity data.<br> Figures are showing the ratio to year 2000 for each of the categories<br> Individual figures are included in the power point for reference and use.<br> Individual figures are also included in the respective excel files</p> <p>Files listed below</p> <ol> <li>coal.consumption.total.xlsx (total coal)</li> <li>electricity.consumption.xlsx (industry, domestic, railways, agriculture, commercial, and total)</li> <li>fuel.consumption.xlsx (LPG, petrol, diesel, kerosene, ATF, others, and petcoke)</li> <li>pass.freight.movement.xlsx (freight as tonne/km and passenger as pass/km)</li> <li>vehicle.registrations.xlsx (2-wheelers+4-wheelers, buses, freight, and all vehicles)</li> </ol>
Code and data used in "A Tool for Air Pollution Scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies"
<p>Data and code for Tool for Air Pollution Scenarios (TAPS v1.0) as submitted to Geoscientific Model Development for publication. See the enclosed README and full user manual (https://github.com/watkin-mit/TAPS/wiki) for more information. </p>
Spatiotemporal variations of air pollution during the COVID-19 pandemic across Tehran, Iran: Commonalities with and differ-ences from global trends
<p>Figure S1: Green space and green area per capita across Tehran; Figure S2: Temporal distribution of CO content at each station, gray rectangular shows strict social distancing time. Figure S3: Temporal distribution of NO2 content in all investigated stations, gray rectangular shows strict social distancing time; Figure S4: Temporal distribution of PM10 content in all investigated stations gray rectangular shows strict social distancing time; Figure S5: Temporal distribution of O3 content in all investigated stations, gray rectangular shows strict social distancing time; Figure S6: Temporal distribution of SO2 content in all investigated stations, gray rectangular shows strict social distancing time; Figure S7: Temporal distribution of AQI indices in all investigated stations, gray rectangular shows strict social distancing time. </p>
Dataset for paper "Marked impacts of pollution mitigation on crop yields in China"
<p>"corn.csv", "winterwheat.csv" and "midlatepaddy.csv" report historical crop yield (unit: kg/hectare)of corn, winter wheat and single cropping rice in China. <br> "regression.ipynb" contains python code to (i) derive the sensitivity of crop yield to climate and pollution variables (ii) compare predicted yield vs. observed yield (iii) calculate the relative contribution of individual climate and pollution variables to inter-annual variations of crop yield. Here we provide the complete datasets for corn in file “organized_data_corn.csv”, which includes air temperature at 2m (t2m), precipitation (tp), aerosol optical depth (aod) and surface ozone (o3) for plant season (plant), growing season (mid) and harvest season (harvest). Please contact us if you are interested in datasets of other two crop species.</p>
РИС. 5. ЗагрЯЗнение готовых обраЗцов длЯ СЭМ при длительном хранении в негерметичных условиЯх (A–C) либо при хранении проШедШих процедуру мацерированиЯ беЗ последуюЩего обеЗЗараживаниЯ (D, E). A–С. Бактерии на поверхности глохидиев (Nodularia douglasiae, р. ИлистаЯ, бассейн оЗ. Ханка, Приморский кр.). А. ВнеШний вид глохидиЯ, основное ЗагрЯЗнение на створке в верхней части фото. В. Крючок глохидиЯ, основное ЗагрЯЗнение в левой части фото. С. Створка, вид иЗнутри. D. Единичные бактерии на створке глохидиЯ, вид иЗнутри (Kunashiria japonica, оЗ. Утиное, о-в Зелёный, Курильские о-ва). E. Гифы гриба на створке глохидиЯ, вид на наружную пору (Beringiana beringiana, оЗ. АЗабачье, Камчатка). МасШтаб 50 мкм (А, C), 10 мкм (В, D), 1 мкм (Е). Микроскопы Zeiss MERLIN (А, B, C, E), Zeiss EVO 40 (D), напыление хромом (А–С), Золотом (D), углеродом (Е). FIG. 5. Contamination of the SEM ready-made samples during long-term storage under unsealed conditions (A–C) or during storage the samples that have passed the maceration procedure without subsequent disinfection (D, E). A–C. Bacteria on the glochidia surface (Nodularia douglasiae, Ilistaya River, Khanka Lake basin, Primorsky Krai). A. Glochidium with the main pollution on the valve in the upper part of the photo. B. Hook with the main pollution on the left side of the photo. C. Interior valve. D. Bacteria on the interior valve (Kunashiria japonica, Utinoe Lake, Zeliony Island, Kuril Islands). E. Fungal hyphae on the pore of exterior valve (Beringiana beringiana, Azabachye Lake, Kamchatka). Scale bars 50 μm (A, C), 10 μm (B, D), 1 μm (E). Zeiss MERLIN (A, B, C, E) and Zeiss EVO 40 (D) microscopes, sputter coating with chromium (A–C), gold (D), and carbon (E). in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе
РИС. 5. ЗагрЯЗнение готовых обраЗцов длЯ СЭМ при длительном хранении в негерметичных условиЯх (A–C) либо при хранении проШедШих процедуру мацерированиЯ беЗ последуюЩего обеЗЗараживаниЯ (D, E). A–С. Бактерии на поверхности глохидиев (Nodularia douglasiae, р. ИлистаЯ, бассейн оЗ. Ханка, Приморский кр.). А. ВнеШний вид глохидиЯ, основное ЗагрЯЗнение на створке в верхней части фото. В. Крючок глохидиЯ, основное ЗагрЯЗнение в левой части фото. С. Створка, вид иЗнутри. D. Единичные бактерии на створке глохидиЯ, вид иЗнутри (Kunashiria japonica, оЗ. Утиное, о-в Зелёный, Курильские о-ва). E. Гифы гриба на створке глохидиЯ, вид на наружную пору (Beringiana beringiana, оЗ. АЗабачье, Камчатка). МасШтаб 50 мкм (А, C), 10 мкм (В, D), 1 мкм (Е). Микроскопы Zeiss MERLIN (А, B, C, E), Zeiss EVO 40 (D), напыление хромом (А–С), Золотом (D), углеродом (Е). FIG. 5. Contamination of the SEM ready-made samples during long-term storage under unsealed conditions (A–C) or during storage the samples that have passed the maceration procedure without subsequent disinfection (D, E). A–C. Bacteria on the glochidia surface (Nodularia douglasiae, Ilistaya River, Khanka Lake basin, Primorsky Krai). A. Glochidium with the main pollution on the valve in the upper part of the photo. B. Hook with the main pollution on the left side of the photo. C. Interior valve. D. Bacteria on the interior valve (Kunashiria japonica, Utinoe Lake, Zeliony Island, Kuril Islands). E. Fungal hyphae on the pore of exterior valve (Beringiana beringiana, Azabachye Lake, Kamchatka). Scale bars 50 μm (A, C), 10 μm (B, D), 1 μm (E). Zeiss MERLIN (A, B, C, E) and Zeiss EVO 40 (D) microscopes, sputter coating with chromium (A–C), gold (D), and carbon (E).
Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants
<p>Freshwaters are highly threatened ecosystems that are vulnerable to chemical pollution and climate change. Freshwater taxa vary in their sensitivity to chemicals and changes in species composition can potentially affect the sensitivity of assemblages to chemical exposure. Here we explore the potential consequences of future climate change on the composition and sensitivity of freshwater macroinvertebrate assemblages to chemical stressors using the UK as a case study.</p> <p>Macroinvertebrate assemblages under end of century (2080-2100) and baseline (1980-2000) climate conditions were predicted for 608 UK sites for four climate scenarios corresponding to mean temperature changes of 1.28°C to 3.78°C. Freshwater macroinvertebrate toxicity data were collated for 19 chemicals and the hierarchical Species Sensitivity Distribution (hSSD) model was used to predict the sensitivity of untested taxa using relatedness within a Bayesian approach. All four future climate scenarios resulted in shifts in assemblage composition, with increases in the prevalence of molluscan, crustacean and annelid species, and towards increasing insect taxa of Odonata, Chironomidae, and Baetidae species. In contrast decreases in were projected for Plecoptera, Ephemeroptera (except for Baetidae) and Coleoptera species.</p> <p>Shifts in taxonomic composition were associated with changes in the percentage of species at risk from chemical exposure. For the 3.78°C climate scenario, 76% of all assemblages became more sensitive to chemicals and for 18 of the 19 chemicals, the percentage of species at risk increased. Climate warming-induced increases in sensitivity were greatest for assemblages exposed to metals and were dependent on baseline assemblage composition, which varied spatially.</p> <p>Climate warming is predicted to result in changes in the use, environmental exposure and toxicity of chemicals. Here we show that, even in the absence of these climate-chemical interactions, shifts in species composition due to climate warming will increase chemical risk and that the impact of chemical pollution on freshwater macroinvertebrate biodiversity may double or quadruple by the end of the 21st century.</p>
Data and code for "Air pollution impacts from warehousing in the United States uncovered with satellite data"
<div> <div> <p>This repository (ver 2024.06.11) contains data and code supporting the analyses and visualizations in the manuscript "Air pollution impacts from warehousing in the United States uncovered with satellite data" in the journal <em>Nature </em><em>Communications</em> (DOI forthcoming). A description of the data files and code can be found in the README. </p> </div> </div>
Fig. 3 in Glass Buildings As Bird Feeders: Urban Birds Exploit Insects Trapped By Polarized Light Pollution
Fig. 3. Timing of foraging visits of European magpie (Pica pica) to the northern building of the Eötvös University as detected by a web camera from 17:00 h on 16 May to 20:00 h on 23 May in 2007. Arrow lengths represent the proportion of all visits made during a particular hour over the
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.