Development of a Multi-Source Satellite Fusion Method for XCH4 Product Generation in Oil and Gas Production Areas DOI Creative Commons
Lu Fan, Yong Wan,

Yongshou Dai

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11100 - 11100

Published: Nov. 28, 2024

Methane (CH4) is the second-largest greenhouse gas contributing to global climate warming. As of 2022, methane emissions from oil and industry amounted 3.586 million tons, representing 13.24% total ranking second among all emission sources. To effectively control in oilfield regions, this study proposes a multi-source remote sensing data fusion method based on concept fusion, targeting high-emission areas such as fields. The aim construct an XCH4 dataset that meets requirements for high resolution, wide coverage, accuracy. Initially, products GOSAT satellite TROPOMI sensor are matched both spatially temporally. Subsequently, variables longitude, latitude, aerosol optical depth, surface albedo, digital elevation model (DEM), month incorporated. Using local random forest (LRF) resulting product combines accuracy with coverage data. On basis, ΔXCH4 derived using GF-5. Combined GFEI prior inventory, high-precision output by LRF redistributed grid areas, producing 1 km resolution product, thereby constructing high-precision, high-resolution regions. Finally, challenges emerged were discussed summarized, it was envisioned that, future, advancement technology algorithms, would be possible obtain more accurate datasets concentration apply range fields, expectation significant contributions could made reducing combating change.

Language: Английский

A hybrid deep learning model based on CNN-GRU-BiLSTM for predicting the carbon removal capacity of the living standing tree using multi-source variables DOI
Zehai Xu,

Qiaoling Han,

Yandong Zhao

et al.

Ecological Modelling, Journal Year: 2025, Volume and Issue: 501, P. 111026 - 111026

Published: Jan. 20, 2025

Language: Английский

Citations

0
Study on the Spatiotemporal Characteristics and Driving Mechanism of Carbon Sink Loss in Hainan Tropical Rainforest National Park Under Typhoon Disturbance DOI

Weiqian He,

Xiaojing Liu,

Donglai Ma

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Differentiation of Carbon Sink Enhancement Potential in the Beijing–Tianjin–Hebei Region of China DOI Creative Commons

Huicai Yang,

Shuqin Zhao,

Zhanfei Qin

et al.

Land, Journal Year: 2024, Volume and Issue: 13(3), P. 375 - 375

Published: March 16, 2024

Carbon sink enhancement is of great significance to achieving carbon peak and neutrality. This study firstly estimated the in Beijing–Tianjin–Hebei Region using absorption coefficient method. Then, this explored differentiation potential with a sink–economic carrying capacity index matrix based on economic under baseline scenario target land use. The results suggested there was remarkable total area, reaching 2,056,400 1,528,300 tons Chengde Zhangjiakou being below 500,000 Langfang Hengshui, while per unit area reached 0.66 ton/ha Qinhuangdao only 0.28 t/ha Tianjin scenario. Increasing optimizing spatial distribution arable land, garden forest, which made greatest contribution sinks, an important way enhancing regional sinks. A hypothetical benchmark city can be constructed according Beijing, comparison for by improving promoting Qinhuangdao, both other cities area.

Language: Английский

Citations

2
Carbon Sink Trends in the Karst Regions of Southwest China: Impacts of Ecological Restoration and Climate Change DOI Creative Commons
Xiaojuan Xu, Fusheng Jiao,

Dayi Lin

et al.

Land, Journal Year: 2023, Volume and Issue: 12(10), P. 1906 - 1906

Published: Oct. 10, 2023

Southwest China (SWC) holds the distinction of being world’s largest rock desertification area. Nevertheless, impacts climate change and ecological restoration projects on carbon sinks in karst area have not been systematically evaluated. In this study, we calculated by utilizing Carnegie–Ames–Stanford Approach (CASA) model, actual measurements, including net primary productivity (NPP) data soil respiration (Rs,) were to obtain sink data. Our findings suggest that areas are displaying increasing trends or positive reversals, accounting for 58.47% area, which is larger than overall average 45.08% China. This suggests a greater sequestration potential. However, approximately 10.42% experience negative reversals. The regions with reversals primarily located western parts Guizhou Guangxi, while observed eastern Chongqing, Guizhou. Ecological main driving factors trends. Increased humidity management reasons sinks. warming drought shift from decreasing east Guangxi study highlight significant role reexamine impact sequestration.

Language: Английский

Citations

5
Development of a Multi-Source Satellite Fusion Method for XCH4 Product Generation in Oil and Gas Production Areas DOI Creative Commons
Lu Fan, Yong Wan,

Yongshou Dai

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(23), P. 11100 - 11100

Published: Nov. 28, 2024

Methane (CH4) is the second-largest greenhouse gas contributing to global climate warming. As of 2022, methane emissions from oil and industry amounted 3.586 million tons, representing 13.24% total ranking second among all emission sources. To effectively control in oilfield regions, this study proposes a multi-source remote sensing data fusion method based on concept fusion, targeting high-emission areas such as fields. The aim construct an XCH4 dataset that meets requirements for high resolution, wide coverage, accuracy. Initially, products GOSAT satellite TROPOMI sensor are matched both spatially temporally. Subsequently, variables longitude, latitude, aerosol optical depth, surface albedo, digital elevation model (DEM), month incorporated. Using local random forest (LRF) resulting product combines accuracy with coverage data. On basis, ΔXCH4 derived using GF-5. Combined GFEI prior inventory, high-precision output by LRF redistributed grid areas, producing 1 km resolution product, thereby constructing high-precision, high-resolution regions. Finally, challenges emerged were discussed summarized, it was envisioned that, future, advancement technology algorithms, would be possible obtain more accurate datasets concentration apply range fields, expectation significant contributions could made reducing combating change.

Language: Английский

Citations

1