Lakes are often described as "hotspots" in the global carbon cycle, yet quantifying their "breath"—the exchange of carbon dioxide (CO2) between water and the atmosphere—has long been notoriously difficult due to extreme variability across time and space and a shortage of long-term, high-resolution observational data. As a result, they have remained a "missing piece" in regional carbon accounting.
To address this gap, a research team led by Profs. HUANG Jiacong and GAO Junfeng from the Nanjing Institute of Geography and Limnology of the Chinese Academy of Sciences, together with collaborators from the Institute of Mountain Hazards and Environment and Jiangxi Normal University, has developed a novel high-resolution machine learning model based on a comprehensive national dataset, enabling high-precision prediction and spatial mapping of CO2 emissions from China's lakes.
The findings were published in Science Advances on April 22.
The study estimates a substantial CO2 emission flux of 11.97 Tg C yr-1 from China's lakes, offsetting roughly 12% of the nation's total wetland carbon sink. While small lakes (<10 km2) exhibit higher emission intensities per unit area (0.29 g C m-2 d-1), large lakes (>50 km2) act as the dominant emission source, contributing 62% of the national total, with strong regional variability ranging from 33% to 79%.
Notably, the study quantifies how lake expansion has affected CO2 emissions between 2000 and 2021. Over this period, annual CO2 emissions from China's lakes rose from 11.25 Tg C to 13.94 Tg C—a 24% increase. This upward trend accelerated after 2010 and is closely associated with sustained lake area expansion, which has ranged from 71 to 462 km2 per year across regions.
The researchers further investigated how extreme climatic events influence lake CO2 emissions. Both extreme heatwaves and intense rainfall events were found to trigger sharp increases in CO2 fluxes, by up to 48% in some regions. With climate change increasing the frequency and severity of such extremes, lake CO2 emissions are projected to continue rising.
"This study underscores the value of high-resolution modeling and long-term observations for carbon accounting at regional and national scales," said Prof. HUANG, corresponding author of the study. "Our findings highlight an urgent need for sustained, high-resolution monitoring to refine lake carbon budgets and inform more effective climate mitigation policies."
