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247 results for “PM2.5”

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dryad32/100

Patterns discovery dataset for particulate matter (pm2.5) pollution trends in Japan

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publicDec 2024View details →
dryad32/100

Automating the interpretation of PM2.5 time-resolved measurements using a data-driven approach

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publicDec 2020View details →
zenodo28/100

Beijing PM2.5 Dataset

<p>This dataset is part of the Monash, UEA &amp;&nbsp;UCR time series regression repository.&nbsp;<a href="http://tseregression.org/">http://tseregression.org/</a></p> <p>The goal of this dataset is to predict PM2.5&nbsp;air quality in the city of Beijing.&nbsp;This dataset contains 17532 time series with 9 dimensions.&nbsp;&nbsp;This includes hourly air pollutants measurments (SO2, NO2, CO and O3), temperature, pressure, dew point, rainfall and windspeed measurments from 12 nationally controlled air quality monitoring sites.&nbsp;The air-quality data are from the Beijing Municipal Environmental Monitoring Center.&nbsp;The meteorological data in each air-quality site are matched with the nearest weather station from the China Meteorological Administration.&nbsp;The time period is from March 1st, 2013 to February 28th, 2017.&nbsp;<br> <br> Please refer to <a href="https://archive.ics.uci.edu/ml/datasets/Beijing+Multi-Site+Air-Quality+Data">https://archive.ics.uci.edu/ml/datasets/Beijing+Multi-Site+Air-Quality+Data</a>&nbsp;for more details<br> <br> Relevant Papers&nbsp;<br> Zhang, S., Guo, B., Dong, A., He, J., Xu, Z. and Chen, S.X. (2017) Cautionary Tales on Air-Quality Improvement in Beijing. Proceedings of the Royal Society A, Volume 473, No. 2205, Pages 20170457&nbsp;<br> <br> Citation Request&nbsp;<br> Zhang, S., Guo, B., Dong, A., He, J., Xu, Z. and Chen, S.X. (2017) Cautionary Tales on Air-Quality Improvement in Beijing. Proceedings of the Royal Society A, Volume 473, No. 2205, Pages 20170457&nbsp;</p>

opencc-by-4.0Jun 2020View details →
zenodo28/100

QFED: Fire-sourced PM2.5 concentrations dataset

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opencc-by-4.0Aug 2024View details →
zenodo28/100

Data and Code for PM2.5 assimilation and health assessment in "Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing"

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opencc-by-4.0Nov 2023View details →
zenodo28/100

chemical composition of PM2.5 in Xindu

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opencc-by-4.0Apr 2024View details →
zenodo28/100

The Impact of COVID-19 on Urban PM2.5 —Taking Hubei Province as an example

<p>Experimental process data</p>

opencc-by-4.0Sep 2021View details →
zenodo28/100

Air pollution knowledge assessments (APnA) - PM2.5 Source Apportionment Results for 50 Indian Cities

<p>Summary of estimated source contributions to ambient PM2.5 concentrations, including the contribution of sources outside the city airsheds. These results are explained and discussed in journal articles.<br> 1.&nbsp;Air pollution knowledge assessments (APnA) for 20 Indian cities [<a href="https://doi.org/10.1016/j.uclim.2018.11.005">link</a>]<br> 2.&nbsp;National Clean Air Programme (NCAP) for Indian cities: Review and outlook of clean air action plans [<a href="https://doi.org/10.1016/j.aeaoa.2020.100096">link</a>]</p> <p>Source descriptions listed in the table<br> A = all transport (road, rail, aviation, and shipping)<br> B = residential<br> C = industries (without brick kilns)<br> D = all dust (construction and resuspension due to vehicle movement)<br> E = open waste burning<br> F = diesel generator sets<br> G = brick manufacturing<br> H = sea salt (where applicable) and<br> I = outside/regional contribution<br> <br> For more information on the model formulation and detailed results by city including summaries of monitoring data, monitoring requirements, points of interest, emission inventories, gridded emissions and pollution maps, and monthly variation in PM2.5 concentrations, visit<br> <a href="https://www.urbanemissions.info/india-apna">https://www.urbanemissions.info/india-apna</a></p>

opencc-by-4.0Feb 2022View details →
zenodo28/100

An approach based on observarion for calculating the local and regional contributions of PM2.5 in Beijing during 2013 to 2020

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opencc-by-4.0May 2024View details →
zenodo28/100

Technical note: Refining δ15N isotopic fingerprints of local NOx for accurate source identification of nitrate in PM2.5

<p>Data</p>

opencc-by-4.0May 2024View details →
zenodo28/100

Resolving organic aerosol components contributing to the oxidative potential of PM2.5 in the North China Plain

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opencc-by-4.0Jun 2024View details →
zenodo28/100

Sources and meteorology influencing highly-time resolved PM2.5 trace elements at 3 urban sites in extremely polluted Indo Gangetic Plain in India, Measurement_Report_Data_21-06-2024

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opencc-by-4.0Jun 2024View details →
zenodo28/100

Data availability for Huai'an PM2.5 data

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opencc-by-4.0Sep 2024View details →
zenodo28/100

The PM2.5 concentration data

<p>The PM<sub>2.5</sub> concentration data</p>

opencc-by-4.0Sep 2021View details →
zenodo28/100

PM2.5 data in Beijing

<p>TOF-ACSM measurements in January - March, 2020 and 2021</p>

opencc-by-4.0Oct 2021View details →
zenodo28/100

2019-2021PM2.5

<p>2019-2021 hourly PM2.5 dataset of Beijing-Heibei-Tianjing(BHT)</p>

opencc-by-4.0Mar 2023View details →
zenodo28/100

Proteinaceous Matter in PM2.5 in a Hilly Basin area, Southwestern China: Decreased Importance in Long-Range Transport and Atmospheric Degradation

<p>Data</p>

opencc-by-4.0May 2023View details →
zenodo28/100

Saudi Arabian PM2.5 concentations

<p>Dataset containing monthly PM2.5 concentrations for the Arabian Peninsula&nbsp;</p>

opencc-by-4.0Aug 2023View details →
zenodo28/100

Unexpected Tradeoffs of Fossil Fuel Reduction on PM2.5 and O3 Pollution Regulation Can be Offset by Synergistic Control of VOCs Source

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opencc-by-4.0Oct 2023View details →
nasa28/100

Simulated Fine Particulate Matter (PM2.5) Estimates over Alaska, 2001-2015

The dataset provides simulated PM2.5 concentration estimates over Alaska, U.S. PM2.5 (particulate matter with diameter <= 2.5 microns) concentrations in air (micrograms m-3) are gridded at 0.1-degree resolution for May to September for the years 2001 through 2015. The data were created in a modeling process utilizing the Wildland Fire Emissions Inventory System (WFEIS), the Arctic-Boreal Vulnerability Experiment (ABoVE) Wildfire Date of Burning (WDoB) dataset, and multiple models including the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The data are provided in GeoTIFF format.

restrictednotspecifiedApr 2025View details →

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Allen Brain Atlas

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DANDI Archive for NWB datasets

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electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
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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.

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Last verified 2026-04-29Open record

OpenNeuro

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neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record