ABSTRACT
Anthropogenic activities exhibit intricate and significant relationships with atmospheric CO2 concentration. Dissecting the spatiotemporal patterns and potential drivers of their coupling coordination relationships from geospatial and temporal perspectives contributes to the benign coordinating development between the two. The coupling coordination degree (D) and types, and their potential influencing factors in China were explored using a coupling coordination model, emerging hotspot analysis, and Multiscale Geographically Weighted Regression model. Results revealed D was dominated by basic coordination in China with notable spatial disparities. Generally, D exhibited higher values in the eastern regions and lower values in the western regions divided by the Hu Line. Furthermore, Central and East China exhibited lower coordination degrees compared to other eastern regions. A total of 15 spatiotemporal dynamic patterns were identified across China. Hot spot patterns were concentrated in the eastern regions of the Hu Line, while cold spots were mainly observed in the western regions. The coupling coordination types exhibited a distinct pattern of "coordination in the east and incoherence in the west, divided by the Hu Line". Over time, there was a shift from lower-level to more benign coordinated types. Additionally, the D and coupling coordination types demonstrated significant spatial agglomeration characteristics, and intercity alliances and enhanced collaborations are essential for sustaining low-carbon improvements. The mechanisms and intensities of various factors on D exhibited spatiotemporal differences. The key drivers influencing coupling coordination types varied depending on the specific type. Additionally, the scales of these drivers affecting D changed over time. It is essential to consider natural and meteorological factors and their scaling effects when developing policies to enhance coupling coordination level. These results have significant implications for assessing the relationship between atmospheric CO2 and human activities and provide guidance for implementing effective low-carbon development policies.
ABSTRACT
Using the Google Earth Engine (GEE) platform, Moderate-resolution image spectroradiometer (MODIS) data of the Weihe River Basin from 2001 to 2021 were acquired, four ecological indicators, namely, greenness, wetness, heat, and dryness, were extracted, and the remote sensing ecological index (RSEI) was constructed through principal component analysis. In addition, the geographic detectors and a multi-scale geographic weighted regression model (MGWR) were used to identify the main driving factors of RSEI changes and capture the differences in spatial changes from different perspectives using multiple indicators. The results show that (1) the quality of the eco-environment in the Weihe River basin improved as a whole from 2001 to 2021, and the RSEI increased from 0.376 to 0.414. In terms of the RSEI grade, the medium RSEI and high RSEI areas increased significantly and the growth rate increased significantly, reaching 26.42% and 27.70%, respectively. (2) Spatially, the quality of the eco-environment in the Weihe River Basin exhibited a spatial distribution pattern that was high in the south and low in the north, among which the quality of the eco-environment in the Weihe River Basin in northern Shaanxi and northwestern Ningxia and Gansu was relatively low. In addition, during the study period, the RSEI of the Qinling Mountains in the southern part of the Weihe River Basin and the Jinghe River and Luohe River areas improved significantly. The urban area on the Guanzhong Plain in the Weihe River Basin experienced rapid economic growth, and urban expansion led to a significant decrease in the quality of the eco-environment. (3) The eco-environment quality in the Weihe River Basin is the result of the interaction of natural, anthropogenic, and landscape pattern factors. All of the interactions between the influencing factors had a stronger influence than those of the individual factors. There were significant differences between the individual drivers and the spatial variation in RSEI, suggesting that different factors dominate the variation in RSEI in different regions, and zonal management is crucial to achieving sustainable management of RSEI. The study shows that to improve the eco-environment quality of the Weihe River Basin, it is necessary to further strengthen ecological protection projects, reasonably allocate landscape elements, and strengthen the resistance and resilience of the ecosystem.