Monitoring spatiotemporal characteristics of land-use carbon emissions and their driving mechanisms in the Yellow River Delta: A grid-scale analysis

Abstract

Comprehensive and accurate grasp of land-use carbon emissions (LCE) level and its driving mechanism is key to success in China's pursuit of low-carbon development, and it is also the scientific basis for the formulation and implementation of regional carbon emissions strategies. Based on fossil fuel carbon emissions raster data (published by the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) platform) and land use data, this manuscript selects the Yellow River Delta as the study area and uses an improved LCE measurement model, exploratory spatial data analysis, multiscale geographical weighting regression (MGWR), and other models to explore the spatiotemporal heterogeneity and driving mechanisms of LCE at the grid level. The results showed the following: ① The total amount of LCE in the study area continued to increase from 2000 to 2019, the growth rate decreased, but the peak of LCE had not yet been reached. ② The LCE of the study area showed a significant positive global autocorrelation. The H–H aggregation region showed a relatively stable spatial distribution range; the L-L aggregation region showed wide distribution characteristics that covered the entire study area; and the aggregation regions of H-L and L-H, which have not yet reached the scale. ③ At the global dimension, the mean correlation coefficients between LCE and driving factors (net primary productivity (NPP), nighttime light (NTL), and population density (PD)) from 2000 to 2019 were −0.11, 0.28, and 0.12; at the local dimension, the strength (from strong to weak) of the effect of each factor on LCE was PD, NTL, NPP (2000) and NTL, PD, NPP (2019). The research results provide a scientific basis and basic guarantee for the development, and implementation of regional carbon emission strategies.