Global decarbonization corresponding with unseasonal land cover change.

ABSTRACT: Understanding the link between unseasonal land cover changes and CO2 emissions can indicate the decarbonization progress of a region, but limited modeling tools exist for analysis in near-real-time. Here, we developed a modeling framework to reveal a strong and robust relationship between the two quantities. By applying the Butterworth filter, unseasonal changes in land cover and fuel-consuming sectors are extracted for Autoregressive Distributed Lag regression analysis in major economies. Among all investigated economies, Russia has demonstrated the strongest co-relationship (R-squared value of 0.730) between unseasonal CO2 emissions and land cover changes, indicative of its heavy reliance on fossil fuels. Both Brazil (1200 km2/MtCO2e on average) and Russia (10,700 km2/MtCO2e) exhibit gre

SUBMITTER: He K 

PROVIDER: S-EPMC12375125 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature