The zero-waste city is one of the most visionary initiatives for solving waste problems by enhancing the life cycle solid waste management system. However, the development level of ZW city construction remains unclear. Resource-based areas tend to produce large amounts of industrial solid waste, and achieving a zero-waste city is difficult due to insufficient resource utilization capacity. This study proposed a practical integrated MCDM approach to assess the performance of the ZW city and applied the approach to a typical coal resource-based province in China. The spatiotemporal characteristics and factors influencing the performance of zero-waste cities in each city were further explored. The performance levels increased during the study period; however, the growth rate of most cities is slow. Spatially, the performance levels of zero-waste cities gradually decreased from south to north, showing a radiation pattern with Taiyuan at its core. Challenges toward zero-waste city development were further identified, including heavy industrial structure, widespread underutilization of industrial solid waste, inadequate management of hazardous solid waste, low rate of urban domestic waste classification, and ineffective treatment. The approach gives a holistic and broader picture of the zero-waste management performance, which enables us to identify the challenges in promoting zero-waste cities.

Shrinking cities are generally experiencing decreases in population, economic activity, and spatial expansion. However, whether this “low-growth” trajectory leads to an actual reduction in carbon emissions or is constrained by carbon lock-in effects and the complex interaction between urban shrinkage and carbon emissions remains unclear. To address this gap, this study examines 34 shrinking cities of the three northeastern provinces in China, utilizing nighttime light data to identify the spatial–temporal patterns of carbon emissions from a multidimensional perspective. Additionally, it explores the key drivers behind these emissions. Results show the following: (1) Spatiotemporally, carbon emissions are closely linked to shrinking cities, which also exhibit spatial–temporal heterogeneity. (2) There is a significant negative spatial correlation between carbon emissions and urban shrinkage degree (SD), with HL clusters (high–low clusters) and LH clusters (low–high clusters) being the main clustering types. (3) Through population, economic, and social driving factors, this paper identifies three synergistic effects shaping spatial–temporal carbon heterogeneity: passive reduction in economic scale (scale effect), volatility effect of structural transformation (structure effect), and spatial–institutional carbon lock-in (lock-in effect). The findings offer new insights into the low-carbon transition potential of shrinking cities and provide a basis for developing targeted policy frameworks to facilitate their sustainable transformation.

ESG (Environmental, Social, and Governance) performance is increasingly viewed as a strategic factor shaping firms’ innovation activities. However, existing studies have largely examined green innovation as a whole, with limited attention to low-carbon technological innovation as a distinct domain and insufficient understanding of its driving mechanisms and conditional heterogeneity. Using panel data on Chinese A-share listed companies from 2009 to 2024, this study employs a two-way fixed-effects framework to examine the effect of ESG performance on low-carbon technological innovation, and further investigates the underlying transmission mechanisms and heterogeneous effects. The results show that ESG significantly promotes low-carbon technological innovation, with a notably stronger effect on substantive innovation than on strategic innovation, indicating that ESG drives genuine technological advancement rather than superficial patent accumulation. Mechanism tests reveal that ESG facilitates innovation by easing financing constraints and enhancing government support. At the dimensional level, the environmental and social pillars exert significant positive effects, whereas the governance pillar does not. Heterogeneity analyses demonstrate that the promotional effect is more pronounced in state-owned enterprises, large firms, heavily polluting industries, and non-technology-intensive firms, revealing structural variation across firm characteristics. By isolating low-carbon innovation from the broader green innovation concept and identifying dual transmission channels, this study extends the literature on the economic consequences of ESG and provides evidence for designing differentiated green governance policies.