Analysis of spatiotemporal patterns of atmospheric CO2 concentration in the Yellow River Basin over the past decade based on time-series remote sensing data DOI

Yang Lv,

MA Yu-chen,

Haoyu Li

et al.

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(54), P. 115745 - 115757

Published: Oct. 27, 2023

Language: Английский

Spatiotemporal Analysis of Atmospheric Methane Concentrations and Key Influencing Factors Using Machine Learning in the Middle East (2010–2021) DOI
Seyed Mohsen Mousavi

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 101406 - 101406

Published: Nov. 1, 2024

Language: Английский

Citations

2

Exploring CO2 anomalies in Brazilian biomes combining OCO-2 & 3 data: Linkages to wildfires patterns DOI
Luis Miguel da Costa, Gustavo André de Araújo Santos, Gislaine Costa de Mendonça

et al.

Advances in Space Research, Journal Year: 2024, Volume and Issue: 73(8), P. 4158 - 4174

Published: Jan. 11, 2024

Language: Английский

Citations

1

Impacts of Spatial Resolution and XCO2 Precision on Satellite Capability for CO2 Plumes Detection DOI Creative Commons
Zhongbin Li, Meng Fan,

Jinhua Tao

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(6), P. 1881 - 1881

Published: March 15, 2024

Greenhouse gas satellites can provide consistently global CO2 data which are important inputs for the top-down inverse estimation of emissions and their dynamic changes. By tracking greenhouse emissions, policymakers businesses identify areas where reductions needed most implement effective strategies to reduce impact on environment. Monitoring gases provides valuable scientists studying climate change. The requirements monitoring verification support capacity drive payload design future satellites. In this study, we quantitatively evaluate performance satellite in detecting plumes from power plants based an improved Gaussian plume model, with focus impacts spatial resolution satellite-derived XCO2 precision under different meteorological conditions. simulations indicate that enhanced significantly improve detection capability satellite, especially small-sized below 6 Mt CO2/yr. satellite-detected maximum enhancement strongly varies wind condition. For a 0.7 ppm 2 km, it recognize plant 2.69 CO2/yr at speed m/s, while its emission needs be larger than 5.1 if is expected detected 4 m/s. Considering uncertainties simulated field, measurements hypothesized cumulative contribution overall accuracy satellite’s ability realistic investigated future. ΔXCO2 caused by uncertainty more significant those introduced direction. case emitting CO2/yr, increasing 0.5 m/s associated field ranges 3.75 ± 2.01 0.46 0.24 1.82 0.95 0.22 0.11 1 × km2 pixel size, respectively. Generally, even direction higher uncertainty, still has direction, because there rapid growth maximal enhancements uncertainties. A designed better km suggested, much likely when 3 Although observed parameters not sufficient full satellites, study insights enhancing anthropogenic emissions.

Language: Английский

Citations

1

Determining the Influence of Meteorological, Environmental, and Anthropogenic Activity Variables on the Atmospheric Co2 Concentration in the Arid and Semi-Arid Regions: A Case Study in the Middle East DOI
Seyed Mohsen Mousavi, Naghmeh Mobarghaee Dinan, Saeed Ansarifard

et al.

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

Citations

0

Analysis of CO2 and air pollutant driving factors and synergistic benefits in typical Chinese industries DOI

Weiyi Du,

Xiahong Shi,

Hanlin Liu

et al.

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 5, 2024

Language: Английский

Citations

0

Analysis of spatiotemporal patterns of atmospheric CO2 concentration in the Yellow River Basin over the past decade based on time-series remote sensing data DOI

Yang Lv,

MA Yu-chen,

Haoyu Li

et al.

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(54), P. 115745 - 115757

Published: Oct. 27, 2023

Language: Английский

Citations

0