Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate change
The large increase of greenhouse gases in the atmosphere, especially carbon dioxide (CO2), is the main cause of global climate change. Studies show that the CO2 exchange processes in the lake switch between the carbon source and the carbon sink action, thus impacting the global carbon cycle. In this...
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Elsevier
2025-09-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X2500994X |
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| author | Ruixue Zhao Zhidan Wen Yingxin Shang Ge Liu Hui Tao Chong Fang Sijia Li Xiangfei Yu Qian Yang Jiping Liu Kaishan Song |
| author_facet | Ruixue Zhao Zhidan Wen Yingxin Shang Ge Liu Hui Tao Chong Fang Sijia Li Xiangfei Yu Qian Yang Jiping Liu Kaishan Song |
| author_sort | Ruixue Zhao |
| collection | DOAJ |
| description | The large increase of greenhouse gases in the atmosphere, especially carbon dioxide (CO2), is the main cause of global climate change. Studies show that the CO2 exchange processes in the lake switch between the carbon source and the carbon sink action, thus impacting the global carbon cycle. In this study, we matched the surface reflectance of Landsat satellite images with the sampling measured partial pressure of carbon dioxide (pCO2) data of northeast lakes from 2016 to 2021, and constructed the pCO2 remote sensing inversion model. The XGBoost model achieved the optimal combination of fitting accuracy and Root Mean Square Error (R2 = 0.86, RMSE = 148.73 μatm) and validation accuracy (R2 = 0.71, RMSE = 186.14 μatm). The model was applied to long-time series remote sensing images for pCO2 inversion analysis of the northeast lakes (area > 1 km2). Final results show that since 1985, the northeast lake average pCO2 change in a downward trend, until 2023, the annual average of pCO2 has been significantly reduced to 363.58 μatm, and small lakes of pCO2 values are higher, large lakes have relatively small pCO2 values. However, chlorophyll a, total suspended matter and turbidity enhanced the overall trend of pCO2, and the water temperature and transparency were negatively correlated with pCO2. With increasing water temperature, lake pCO2 usually decreases. This study speculated that temperature, water quality and lake biodiversity changes would affect the average pCO2 of northeast lakes. The results are important for a deeper understanding of lakes in the global carbon cycle and the process of climate change. |
| format | Article |
| id | doaj-art-149a4a35aff94cceac7f696630d51f25 |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-149a4a35aff94cceac7f696630d51f252025-08-20T05:04:54ZengElsevierEcological Indicators1470-160X2025-09-0117811406210.1016/j.ecolind.2025.114062Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate changeRuixue Zhao0Zhidan Wen1Yingxin Shang2Ge Liu3Hui Tao4Chong Fang5Sijia Li6Xiangfei Yu7Qian Yang8Jiping Liu9Kaishan Song10State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China; Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing 100094, ChinaState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China; Corresponding authors at: Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China; Corresponding authors at: Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, ChinaState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, ChinaState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, ChinaState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, ChinaJilin Jianzhu University, Changchun 130000, ChinaState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, ChinaCollege of Geographical Science and Tourism, Jilin Normal University, Siping 136000, ChinaState Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, ChinaThe large increase of greenhouse gases in the atmosphere, especially carbon dioxide (CO2), is the main cause of global climate change. Studies show that the CO2 exchange processes in the lake switch between the carbon source and the carbon sink action, thus impacting the global carbon cycle. In this study, we matched the surface reflectance of Landsat satellite images with the sampling measured partial pressure of carbon dioxide (pCO2) data of northeast lakes from 2016 to 2021, and constructed the pCO2 remote sensing inversion model. The XGBoost model achieved the optimal combination of fitting accuracy and Root Mean Square Error (R2 = 0.86, RMSE = 148.73 μatm) and validation accuracy (R2 = 0.71, RMSE = 186.14 μatm). The model was applied to long-time series remote sensing images for pCO2 inversion analysis of the northeast lakes (area > 1 km2). Final results show that since 1985, the northeast lake average pCO2 change in a downward trend, until 2023, the annual average of pCO2 has been significantly reduced to 363.58 μatm, and small lakes of pCO2 values are higher, large lakes have relatively small pCO2 values. However, chlorophyll a, total suspended matter and turbidity enhanced the overall trend of pCO2, and the water temperature and transparency were negatively correlated with pCO2. With increasing water temperature, lake pCO2 usually decreases. This study speculated that temperature, water quality and lake biodiversity changes would affect the average pCO2 of northeast lakes. The results are important for a deeper understanding of lakes in the global carbon cycle and the process of climate change.http://www.sciencedirect.com/science/article/pii/S1470160X2500994XCO2pCO2Carbon emissionsRemote sensingNortheast lakes |
| spellingShingle | Ruixue Zhao Zhidan Wen Yingxin Shang Ge Liu Hui Tao Chong Fang Sijia Li Xiangfei Yu Qian Yang Jiping Liu Kaishan Song Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate change Ecological Indicators CO2 pCO2 Carbon emissions Remote sensing Northeast lakes |
| title | Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate change |
| title_full | Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate change |
| title_fullStr | Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate change |
| title_full_unstemmed | Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate change |
| title_short | Satellite estimation of pCO2 and quantification of CO2 fluxes in lakes in the context of climate change |
| title_sort | satellite estimation of pco2 and quantification of co2 fluxes in lakes in the context of climate change |
| topic | CO2 pCO2 Carbon emissions Remote sensing Northeast lakes |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X2500994X |
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