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The moving-window Bayesian maximum entropy framework: estimation of PM2.5 yearly average concentration across the contiguous United States

UNC Libraries(2020)10.17615/13qr-b422Source: DataRank Database

The moving-window Bayesian maximum entropy framework: estimation of PM2.5 yearly average concentration across the contiguous United States is a research paper published in UNC Libraries (2020). On theSindex it has a DataRank of 0.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (2 grants)Impact (FWCI 0.00)OA: greenTopics (26)IDs (PubMed, OpenAlex)SDGs (3)

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Accessible (1/2)

Open Access

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Reusable (0/3)

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Authors (3)

Marc L. Serre ORCID,Akita, Yasuyuki,Jiu‐Chiuan Chen

Live enrichment

PubMed:21097893 OpenAlex:https://openalex.org/W4300635332

National Institutes of Health

Grant: 1R21HL089422-01

Environmental Determinants of Sleep Disturbance: Role of Ambient Air Pollution

National Institutes of Health

Grant: 5R01AG033078-02

Environmental Determinants of Cognitive Aging in the WHI Memory Study

FWCI

0.00

Citation Percentile

0.2%

greenLicense: Springer TDM

repositoryhttps://doi.org/10.17615/13qr-b422

https://doi.org/10.1038/jes.2012.57

https://www.nature.com/articles/jes201257.pdf

https://dx.doi.org/10.17615/13qr-b422

https://pubmed.ncbi.nlm.nih.gov/22739679

Fields of Study

Air Quality Monitoring and ForecastingAir Quality and Health ImpactsVehicle emissions and performance01 natural sciences0105 earth and related environmental sciences

Keywords

Bayesian probabilityWindow (computing)EstimationStatisticsPrinciple of maximum entropyEnvironmental scienceEntropy (arrow of time)EconometricsMathematicsMeteorologyGeographyComputer scienceEngineeringPhysicsModels, StatisticalAir PollutionHumansBayes TheoremParticulate MatterUnited StatesEnvironmental Monitoring

Sustainable Development Goals

SDG 11: 11. SustainabilitySDG 13: 13. Climate actionSDG 0: Climate action