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24 results for “Fine particulate matter”
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.
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>
Daily Emission of Fine Particulate Matter (PM2.5) Associated with Biomass Burning in South America During 2002-2020
<p>The dataset "Daily Emission of Fine Particulate Matter (PM2.5) Associated with Biomass Burning in South America During 2002-2020" contains the emissions analysed in the manuscript "Updated Land Use and Land Cover Information Improves Biomass Burning Emission Estimates", published in Fire 2023, 6(11), 426; <a href="https://doi.org/10.3390/fire6110426">https://doi.org/10.3390/fire6110426</a>.</p>
Population impact of fine particulate matter on tuberculosis risk in China: A causal inference
<p>Supplementary to "Population impact of fine particulate matter on tuberculosis risk in China: A causal inference"</p>
Decoding Physical and Cognitive Impacts of Particulate Matter Concentrations at Ultra-fine Scales
<p>Data, plots, and software to accompany (unpublished) paper: Decoding Physical and Cognitive Impacts of Particulate Matter Concentrations at Ultra-fine Scales. This work uses an ultra-fine, holistic environmental and biometric sensing paradigm to generate empirical particulate matter models estimated by biometric variables.</p> <p>GitHub repository: <a href="https://github.com/mi3nts/DUEDARE">https://github.com/mi3nts/DUEDARE</a></p>
Towards improving short-term predictions of fine particulate matter over the United States via assimilation of satellite aerosol optical depth retrievals
<p>This dataset contains paired modeled and observed values of different trace gases and aerosol species over the CONUS for the period of 15 July to 14 August 2014 for the three different data assimilation experiments (BKG, MET_BE and MET+EMIS_BE) described in the paper. </p>
Effect of meteorological variability on fine particulate matter simulations over the contiguous United States
<p>Supporting data files for the paper titled "Effect of meteorological variability on fine particulate matter simulations over the contiguous United States" submitted to JGR-Atmosphere for publication.</p>
Biomass burning in the Neotropics is exposing migrating birds to elevated fine particulate matter concentrations
<p><strong>Aim</strong>: A unique risk faced by nocturnally migrating birds is the disorienting influence of artificial light at night (ALAN). ALAN originates from anthropogenic activities that can generate other forms of environmental pollution, including the emission of fine particulate matter (PM<sub>2.5</sub>). PM<sub>2.5</sub> concentrations can display strong seasonal variation originating from natural and anthropogenic processes. How these processes affect seasonal associations with ALAN and PM<sub>2.5</sub> for nocturnally migrating birds has not been documented.</p> <p><strong>Location</strong>: Western Hemisphere</p> <p><strong>Time</strong> <strong>period</strong>: 2021</p> <p><strong>Major taxa studied</strong>: Nocturnally migrating passerine (NMP) bird species</p> <p><strong>Methods</strong>: We combined monthly estimates of PM<sub>2.5</sub> and ALAN with weekly estimates of relative abundance for 164 NMP species within the Western Hemisphere derived using bird observations from eBird. We identify groups of species with shared associations with PM<sub>2.5</sub>.</p> <p><strong>Results</strong>: PM<sub>2.5</sub> was lowest in North America, especially at higher latitudes during the boreal winter. PM<sub>2.5</sub> was highest in the Amazon Basin, especially during the dry season (August-October). ALAN was highest within eastern North America, especially during the boreal winter. For the NMP species, PM<sub>2.5</sub> associations reached their lowest levels during the breeding season (<10 μg/m<sup>3</sup>) and highest levels during the nonbreeding season, especially for species that winter in Central and South America (~20 μg/m<sup>3</sup>). Species that migrate through Central America in the spring encountered similarly high PM<sub>2.5 </sub>concentrations. ALAN associations reached their highest levels for species that migrate (~12 nW/cm<sup>2</sup>/sr) or spend the nonbreeding season (~15 nW/cm<sup>2</sup>/sr) in eastern North America.</p> <p><strong>Main conclusions</strong>: We did not find evidence that the disorienting influence of ALAN enhances PM<sub>2.5</sub> exposure during stopover in the spring and autumn for NMP species. Rather, our findings suggest biomass burning in the Neotropics is exposing NMP species to consistently elevated PM<sub>2.5</sub> concentrations for an extended period of their annual life cycles. </p>
Biomass burning in the Neotropics is exposing migrating birds to elevated fine particulate matter concentrations
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Fine particulate matter and neuroanatomic risk for Alzheimer's disease in older women
<div class="WordSection1"> <div class="WordSection1"> <p><strong>Objective</strong>: To examine whether late-life exposure to PM<sub>2.5</sub> (particulate matter with aerodynamic diameters <2.5-µm) contributes to progressive brain atrophy predictive of Alzheimer's disease (AD) using a community-dwelling cohort of women (aged 71-89) with up to two brain MRI scans (MRI-1: 2005-6; MRI-2: 2010-11).</p> <p><strong>Methods</strong>: AD pattern similarity (AD-PS) scores, developed by supervised machine learning and validated with MRI data from the AD Neuroimaging Initiative, was used to capture high-dimensional gray matter atrophy in brain areas vulnerable to AD (e.g., amygdala, hippocampus, parahippocampal gyrus, thalamus, inferior temporal lobe areas and midbrain). Based on participants' addresses and air monitoring data, we employed a spatiotemporal model to estimate 3-year average exposure to PM<sub>2.5</sub> preceding MRI-1. General linear models were used to examine the association between PM<sub>2.5</sub> and AD-PS scores (baseline [n=1365] and 5-year standardized change [n=712]), accounting for potential confounders and white matter lesion volumes.</p> <p><strong>Results</strong>: There was no association between PM<sub>2.5</sub> and baseline AD-PS score in cross-sectional analyses. Longitudinally, each interquartile range increase of PM<sub>2.5</sub> (2.82-µg/m3) was associated with increased AD-PS scores during the follow-up, equivalent to a 24% (hazard ratio=1.24; 95% CI: 1.14, 1.34) increase in AD risk over 5-years. This association remained after adjustment for socio-demographics, intracranial volume, lifestyle, clinical characteristics, and white matter lesions, and was present with levels below US regulatory standards (<12-µg/m3).</p> <p><strong>Conclusions</strong>: Late-life exposure to PM<sub>2.5</sub> is associated with increased neuroanatomical risk of AD, which may not be explained by available indicators of cerebrovascular damage.</p> </div> </div>
Data from: Early postnatal exposure to airborne fine particulate matter induces autism-like phenotypes in male rats
Epidemiological studies have revealed that ambient fine particulate matter (PM2.5) exposure is closely associated with autism spectrum disorder (ASD). However, there is a relative paucity of laboratory data to support this epidemic finding. In order to assess the relationship between PM2.5 exposure and ASD, neonatal male Sprague-Dawley (SD) rats were chosen and exposed to PM2.5 (2 or 20 mg/kg body weight, once a day) by intranasal instillation from postnatal day (PND) 8 to 22. It was found that when exposed to PM2.5 in the early neonatal period for two weeks, both groups of the exposure rats manifested typical behavioral features of autism, including communication deficits, poor social interaction and novelty avoidance. And, we further found, among five ASD candidate genes we chose, both the mRNA level and protein expression of SH3 and multiple ankyrin repeat domains 3 (Shank3) decreased significantly in the rat hippocampus after high dose of PM2.5 exposure. Moreover, results showed that PM2.5-exposure significantly increased the levels of pro-inflammatory cytokines, IL-1β, IL-6, and TNF-α in the hippocampus and prefrontal cortex. The expression of Glial fibrillary acidic protein (GFAP) and ionized binding calcium adapter molecule (IBA1), markers of astrocytes and microglial cell activation, respectively, also increased in the exposed animals. Our work provides new data on the link between postnatal exposure to ambient PM2.5 and the onset of ASD-like symptoms in human beings, and the increased inflammatory response and abnormalities in Shank3 expression in the brain may contribute to the mechanisms of PM2.5 exposure induced ASD.
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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Data and code for the paper: Exposure to Fine Particulate Matter during Home-to-Work Commute in the New York City Subway System
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Input data and analysis codes for "Reversal of trends in global fine particulate matter air pollution"
<p>This dataset contains Input data and analysis codes used for the following article:</p> <p>Li, C., A. van Donkelaar, M. S. Hammer, E. E. McDuffie, R. T. Burnett, J. V. Spadaro, D. Chatterjee, A. J. Cohen, J. S. Apte, V. A. Southerland, S. C. Anenberg, M. Brauer, & R. V. Martin, Reversal of trends in global fine particulate matter air pollution, submitted, 2023.</p> <p> </p> <p><strong>Input Data</strong></p> <p>Baseline mortality data (204 countries and territories, 17 age groups, 6 diseases, 22 years)</p> <p>Concentration-response functions (GEMM and MRBRT)</p> <p>PM<sub>2.5</sub> exposure for 204 territories and 22 years</p> <p>Age-specific population for 204 territories and 22 years</p> <p> </p> <p><strong>Derived Data</strong></p> <p>Age- and disease-specific PM<sub>2.5</sub>-attributable Mortality estimates for 204 territories and 22 years.</p> <p>Sensitivity of PM<sub>2.5</sub>-attributable Mortality to marginal PM<sub>2.5</sub> reduction for 204 territories and 22 years.</p> <p>Attributable of changes in PM<sub>2.5</sub>-attributable Mortality (and its sensitivity to marginal PM<sub>2.5</sub> reduction) to four driving factors.</p> <p> </p> <p><strong>Code</strong></p> <p>Necessary python scripts to verify and replicate analysis results in the manuscript.</p>
Data from: Early postnatal exposure to airborne fine particulate matter induces autism-like phenotypes in male rats
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Fine particulate matter and neuroanatomic risk for Alzheimer’s disease in older women
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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.
Fine particulate matter (PM2.5) induces microRNA-192–5p causing glomerular damage
GEO Series GSE285038. Danio rerio. 4 samples. Type: Expression profiling by high throughput sequencing.
RNA-seq analysis identifies the impact of different organic components of fine particulate matter (PM2.5) on human nasal fibroblasts
GEO Series GSE284720. Homo sapiens. 15 samples. Type: Expression profiling by high throughput sequencing.
Airborne Ultrafine and Fine Particulate Matter: A Cause for Endothelial Dysfunction in Man?
ClinicalTrials.gov study NCT00814281. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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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.