(PDF) Fine Particulate Matter (PM<sub

Fine Particulate Matter (PM2.5) Trends in China, 2013–2018: Separating Contributions From Anthropogenic Emissions and Meteorology

Atmospheric Chemistry and Physics - Germany

doi 10.5194/acp-19-11031-2019

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August 29, 2019

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Copernicus GmbH

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Amanote Research

Fine Particulate Matter (PM<sub>2.5</sub>) Trends in China, 2013–2018: Separating Contributions From Anthropogenic Emissions and Meteorology

Atmospheric Chemistry and Physics - Germany

doi 10.5194/acp-19-11031-2019

Full Text

Abstract

Categories

Date

Authors

Publisher

Related search

Sources and Oxidative Potential of Water-Soluble Humic-Like Substances (HULIS<sub>WS</sub>) in Fine Particulate Matter (PM<sub>2.5</sub>) in Beijing

Source Sector and Region Contributions to Black Carbon and PM<sub>2.5</sub> In the Arctic

Fungi Diversity in PM<sub>1</sub> And PM<sub>2.5</sub> At the Summit of Mt. Tai: Abundance, Size Distribution, and Seasonal Variation

Retrospective Analysis of 2015–2017 Wintertime PM<sub>2.5</sub> In China: Response to Emission Regulations and the Role of Meteorology

Development of Daily PM<sub>10</sub> And PM<sub>2.5</sub> Prediction System Using a Deep Long Short-Term Memory Neural Network Model

Development of Daily PM<sub>10</sub> And PM<sub>2.5</sub> Prediction System Using a Deep Long Short-Term Memory Neural Network Model

Synthesis and Piezoelectric Properties of Pb<sub>0.98</Sub>Sm<sub>0.02</Sub>[(Zr<sub>y</Sub>,Ti<sub>1–y</Sub>)<sub>0.98</Sub>(Fe<sub>1/2</Sub><sup>3+</Sup>,Nb<sub>1/2</Sub><sup>5+</Sup>)<sub>0.02</Sub>]O<sub>3</Sub> Ceramics

Sectorial and Regional Uncertainty Analysis of the Contribution of Anthropogenic Emissions to Regional and Global PM<sub>2.5</sub> Health Impacts

Crystallization of Hydrosodalite Na<sub>6</Sub>[AlSiO<sub>4</Sub>]<sub>6</Sub>(H<sub>2</Sub>O)<sub>8</Sub> And Tetrahydroborate Sodalite Na<sub>8</Sub>[AlSiO<sub>4</Sub>]<sub>6</Sub>(BH<sub>4</Sub>)<sub>2</Sub> Inside the Openings of Wafer-Thin Steel Mes

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Fine Particulate Matter (PM&lt;sub&gt;2.5&lt;/sub&gt;) Trends in China, 2013–2018: Separating Contributions From Anthropogenic Emissions and Meteorology

Atmospheric Chemistry and Physics - Germany

doi 10.5194/acp-19-11031-2019

Full Text

Abstract

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Date

Authors

Publisher

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Sources and Oxidative Potential of Water-Soluble Humic-Like Substances (HULIS&lt;sub&gt;WS&lt;/sub&gt;) in Fine Particulate Matter (PM&lt;sub&gt;2.5&lt;/sub&gt;) in Beijing

Source Sector and Region Contributions to Black Carbon and PM&lt;sub&gt;2.5&lt;/sub&gt; In the Arctic

Fungi Diversity in PM&lt;sub&gt;1&lt;/sub&gt; And PM&lt;sub&gt;2.5&lt;/sub&gt; At the Summit of Mt. Tai: Abundance, Size Distribution, and Seasonal Variation

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Development of Daily PM&lt;sub&gt;10&lt;/sub&gt; And PM&lt;sub&gt;2.5&lt;/sub&gt; Prediction System Using a Deep Long Short-Term Memory Neural Network Model

Sectorial and Regional Uncertainty Analysis of the Contribution of Anthropogenic Emissions to Regional and Global PM&lt;sub&gt;2.5&lt;/sub&gt; Health Impacts

Fine Particulate Matter (PM<sub>2.5</sub>) Trends in China, 2013–2018: Separating Contributions From Anthropogenic Emissions and Meteorology

Sources and Oxidative Potential of Water-Soluble Humic-Like Substances (HULIS<sub>WS</sub>) in Fine Particulate Matter (PM<sub>2.5</sub>) in Beijing

Source Sector and Region Contributions to Black Carbon and PM<sub>2.5</sub> In the Arctic

Fungi Diversity in PM<sub>1</sub> And PM<sub>2.5</sub> At the Summit of Mt. Tai: Abundance, Size Distribution, and Seasonal Variation

Retrospective Analysis of 2015–2017 Wintertime PM<sub>2.5</sub> In China: Response to Emission Regulations and the Role of Meteorology

Development of Daily PM<sub>10</sub> And PM<sub>2.5</sub> Prediction System Using a Deep Long Short-Term Memory Neural Network Model

Development of Daily PM<sub>10</sub> And PM<sub>2.5</sub> Prediction System Using a Deep Long Short-Term Memory Neural Network Model

Sectorial and Regional Uncertainty Analysis of the Contribution of Anthropogenic Emissions to Regional and Global PM<sub>2.5</sub> Health Impacts