Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Mengya Sheng"'
Publikováno v:
Remote Sensing, Vol 16, Iss 13, p 2456 (2024)
The spatial and temporal variations in the atmospheric CO2 concentrations evidently respond to anthropogenic CO2 emission activities. NO2, a pollutant gas emitted from fossil fuel combustion, comes from the same emission sources as CO2. Exploiting th
Externí odkaz:
https://doaj.org/article/1a7845b02b9c41a38d484b8d90ecf606
Publikováno v:
Atmosphere, Vol 15, Iss 3, p 323 (2024)
The monitoring of anthropogenic CO2 emissions, which increase the atmospheric CO2 concentration, plays the most important role in the management of emission reduction and control. With the massive increase in satellite-based observation data related
Externí odkaz:
https://doaj.org/article/f581a958dbde46d68baa42f037c1b8b3
Publikováno v:
Big Earth Data, Vol 0, Iss 0, Pp 1-21 (2022)
A global mapping data of atmospheric carbon dioxide (CO2) concentrations can help us to better understand the spatiotemporal variations of CO2 and the driving factors of the variations to support the actions for emissions reduction and control. Green
Externí odkaz:
https://doaj.org/article/197094e02ddd4ea6bc3921f042de4b12
Publikováno v:
Remote Sensing, Vol 15, Iss 13, p 3389 (2023)
Space-based measurements, such as the Greenhouse gases Observing SATellite (GOSAT) and the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite, provide global observations of the column-averaged CH4 concentration (X
Externí odkaz:
https://doaj.org/article/a0f6eb0207ac4afc813f3447d91bb980
Autor:
Shaoqing Zhang, Liping Lei, Mengya Sheng, Hao Song, Luman Li, Kaiyuan Guo, Caihong Ma, Liangyun Liu, Zhaocheng Zeng
Publikováno v:
Remote Sensing, Vol 14, Iss 19, p 5024 (2022)
Anthropogenic carbon dioxide (CO2) emissions from bottom-up inventories have high uncertainties due to the usage of proxy data in creating these inventories. To evaluate bottom-up inventories, satellite observations of atmospheric CO2 with continuous
Externí odkaz:
https://doaj.org/article/9258684459594105b4a647f87c185b3a
Publikováno v:
Remote Sensing, Vol 13, Iss 17, p 3524 (2021)
The continuing increase in atmospheric CO2 concentration caused by anthropogenic CO2 emissions significantly contributes to climate change driven by global warming. Satellite measurements of long-term CO2 data with global coverage improve our underst
Externí odkaz:
https://doaj.org/article/b1c679fda1124ba59f4dd737dc100c1c
Publikováno v:
Remote Sensing, Vol 12, Iss 4, p 718 (2020)
Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these re
Externí odkaz:
https://doaj.org/article/66b5b43687b74d49a9623b040abd2d64
Autor:
Zhonghua He, Liping Lei, Yuhui Zhang, Mengya Sheng, Changjiang Wu, Liang Li, Zhao-Cheng Zeng, Lisa R. Welp
Publikováno v:
Remote Sensing, Vol 12, Iss 3, p 576 (2020)
Column-averaged dry air mole fraction of atmospheric CO2 (XCO2), obtained by multiple satellite observations since 2003 such as ENVISAT/SCIAMACHY, GOSAT, and OCO-2 satellite, is valuable for understanding the spatio-temporal variations of atmospheric
Externí odkaz:
https://doaj.org/article/7b1c91973b414f5db4fd6406bdfb3714
Publikováno v:
Remote Sensing; Volume 15; Issue 13; Pages: 3389
Space-based measurements, such as the Greenhouse gases Observing SATellite (GOSAT) and the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite, provide global observations of the column-averaged CH4 concentration (X
Autor:
Mengya Sheng, Liang Li, Zhao-Cheng Zeng, Lisa R. Welp, Changjiang Wu, Liping Lei, Yuhui Zhang, Zhonghua He
Publikováno v:
Remote Sensing
Volume 12
Issue 3
Pages: 576
Remote Sensing, Vol 12, Iss 3, p 576 (2020)
Volume 12
Issue 3
Pages: 576
Remote Sensing, Vol 12, Iss 3, p 576 (2020)
Column-averaged dry air mole fraction of atmospheric CO2 (XCO2), obtained by multiple satellite observations since 2003 such as ENVISAT/SCIAMACHY, GOSAT, and OCO-2 satellite, is valuable for understanding the spatio-temporal variations of atmospheric