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Accurate assessment of the sustainable development level is crucial to providing reasonable and effective management recommendations. However, analysis with a single scale can only reflect the sustainable status at a specific level. In this study, a multi-scale analysis of sustainability was conducted via the three-dimensional Ecological Footprint (EF) model in the Yangtze River Delta (YRD). Moreover, driving factors of sustainability were analyzed using the Multi-scale Geographically Weighted Regression model (MGWR). The conclusions include: (1) the development of YRD showed an unsustainable trend from 2014 to 2021, with per capita EF decreasing from 5.769 ha/cap to 5.283 ha/cap. The provincial sustainability is ranked as follows, from being the most sustainable to the least: Anhui Province > Jiangsu Province > Zhejiang Province > Shanghai City. (2) Based on dual indicators of EF depth and size, 41 cities were categorized into nine groups. The dominant type is always Medium size-Low depth (ML) and High size-Low depth (HL) type cities from 2014 to 2021. From the perspective of city scale, the sustainability of five cities weakened, while seven cities showed improvements. (3) Output value of primary industry (OVPI) and population (POP) were always the dominant factors affecting EF, but showed positive and negative correlations respectively. OVPI changes from north-south symmetric type to central symmetric type, while POP changes from central symmetric type to north-south symmetric type. This paper aims to comprehensively assess the sustainable development status from agglomeration-province-city perspectives, and its findings can provide a reference for similar regions with unbalanced development status between ecology and production. • The sustainability of the world-class urban agglomeration was assessed via the three-dimensional ecological footprint model. • More comprehensive and accurate analysis results based on multi-scale analysis. • The four patterns of influencing mechanism are revealed based on the MGWR model. • The combination analysis of dual indicators was adopted to classify the sustainability of 41 cities. [ABSTRACT FROM AUTHOR]

Carbon emissions (CE) have a profound impact on the natural environment of the surface, and the ecologic environment quality (EEQ) affects the conversion and absorption of CE. CE and EEQ have an interaction and mutual influence relationship. The connection between them includes not only local interactions but also the long-range distance of external systems. It is critical to measure CE and EEQ and coordinate their association in order to increase the effectiveness of CE and EEQ collaborative governance. However, the traditional remote sensing ecological index (RSEI) model ignores the importance of air quality. Furthermore, there is limited current research on the local and telecoupling relationship between CE and the EEQ. To fill these research gaps, this paper first used night light data to dynamically monitor CE. Then we proposed an upgraded RSEI model (RSEInew) to assess EEQ. Finally, the local and telecoupling coordination degree (LTCCD) model was suggested to further investigate their relationship in the Yangtze River Economic Belt (YREB) from 2000 to 2019. The results showed that: (1) Total CE in the YREB increased from 837.5738 million tons to 4757.3794 million tons between 2000 and 2019 but has not yet reached its peak. Jiangsu and Zhejiang are at the forefront in terms of CE and have huge emission reduction potential. (2) The YREB's overall EEQ has deteriorated over the last 20 years. The average RSEInew value ranged between 0.52 and 0.71, with "medium" and "good" EEQ levels dominating. (3) The LTCCD of CE and EEQ in the YREB has increased year by year. This study can deliver a reference for decision-makers to synergistically formulate carbon emission reduction plans and environmental protection schemes. • Ecologic environment quality should combine regional characteristics, our RSEInew model could evaluate it with introduces PM2.5. • Carbon emissions and the ecologic environment quality interact with each other, with near- and long-range interactions. • The LTCCD model enable to analysis the local and telecoupling relationships of CE and EEQ. [ABSTRACT FROM AUTHOR]