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Estimating Ground‐Level PM2.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach
Estimating Ground‐Level PM2.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach
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Estimating Ground‐Level PM2.5 by Fusing Satellite and Station Observations: A Geo‐Intelligent Deep Learning Approach

Li, Tongwen ; Shen, Huanfeng ; Yuan, Qiangqiang ; Zhang, Xuechen ; Zhang, Liangpei

Geophysical research letters, 2017-12, Vol.44 (23), p.11,985-11,993 [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors
Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors
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Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors

Pope, Francis D. ; Gatari, Michael ; Ng'ang'a, David ; Poynter, Alexander ; Blake, Rhiannon

Atmospheric chemistry and physics, 2018-10, Vol.18 (20), p.15403-15418 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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3
Strategies of method selection for fine-scale PM2.5 mapping in an intra-urban area using crowdsourced monitoring
Strategies of method selection for fine-scale PM2.5 mapping in an intra-urban area using crowdsourced monitoring
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Strategies of method selection for fine-scale PM2.5 mapping in an intra-urban area using crowdsourced monitoring

Xu, Shan ; Zou, Bin ; Lin, Yan ; Zhao, Xiuge ; Li, Shenxin ; Hu, Chenxia

Atmospheric measurement techniques, 2019-05, Vol.12 (5), p.2933-2948 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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4
One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system
One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system
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One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

Hu, Jianlin ; Chen, Jianjun ; Ying, Qi ; Zhang, Hongliang

Atmospheric chemistry and physics, 2016-08, Vol.16 (16), p.10333-10350 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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5
A Review on Air Quality Measurement Using an Unmanned Aerial Vehicle
A Review on Air Quality Measurement Using an Unmanned Aerial Vehicle
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A Review on Air Quality Measurement Using an Unmanned Aerial Vehicle

Lambey, Vinit ; Prasad, A. D.

Water, air, and soil pollution, 2021-03, Vol.232 (3), Article 109 [Periódico revisado por pares]

Cham: Springer International Publishing

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6
Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire
Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire
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Are dense networks of low-cost nodes really useful for monitoring air pollution? A case study in Staffordshire

Frederickson, Louise Bøge ; Sidaraviciute, Ruta ; Schmidt, Johan Albrecht ; Hertel, Ole ; Johnson, Matthew Stanley

Atmospheric chemistry and physics, 2022-11, Vol.22 (21), p.13949-13965 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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7
Concentrations of criteria pollutants in the contiguous U.S., 1979 - 2015: Role of prediction model parsimony in integrated empirical geographic regression
Concentrations of criteria pollutants in the contiguous U.S., 1979 - 2015: Role of prediction model parsimony in integrated empirical geographic regression
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Concentrations of criteria pollutants in the contiguous U.S., 1979 - 2015: Role of prediction model parsimony in integrated empirical geographic regression

Kim, Sun-Young ; Bechle, Matthew ; Hankey, Steve ; Sheppard, Lianne ; Szpiro, Adam A ; Marshall, Julian D Giorgi, Emanuele

PloS one, 2020-02, Vol.15 (2), p.e0228535 [Periódico revisado por pares]

United States: Public Library of Science

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8
A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC
A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC
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A 6-year-long (2013–2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC

Kong, Lei ; Tang, Xiao ; Zhu, Jiang ; Wang, Zifa ; Li, Jianjun ; Wu, Huangjian ; Wu, Qizhong ; Chen, Huansheng ; Zhu, Lili ; Wang, Wei ; Liu, Bing ; Wang, Qian ; Chen, Duohong ; Pan, Yuepeng ; Song, Tao ; Li, Fei ; Zheng, Haitao ; Jia, Guanglin ; Lu, Miaomiao ; Wu, Lin ; Carmichael, Gregory R

Earth system science data, 2021-02, Vol.13 (2), p.529-570 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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9
Low-Cost Sensor Node for Air Quality Monitoring: Field Tests and Validation of Particulate Matter Measurements
Low-Cost Sensor Node for Air Quality Monitoring: Field Tests and Validation of Particulate Matter Measurements
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Low-Cost Sensor Node for Air Quality Monitoring: Field Tests and Validation of Particulate Matter Measurements

Schilt, Ueli ; Barahona, Braulio ; Buck, Roger ; Meyer, Patrick ; Kappani, Prince ; Möckli, Yannis ; Meyer, Markus ; Schuetz, Philipp

Sensors (Basel, Switzerland), 2023-01, Vol.23 (2), p.794 [Periódico revisado por pares]

Switzerland: MDPI AG

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10
The Response in Air Quality to the Reduction of Chinese Economic Activities During the COVID‐19 Outbreak
The Response in Air Quality to the Reduction of Chinese Economic Activities During the COVID‐19 Outbreak
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The Response in Air Quality to the Reduction of Chinese Economic Activities During the COVID‐19 Outbreak

Shi, Xiaoqin ; Brasseur, Guy P.

Geophysical research letters, 2020-06, Vol.47 (11), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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