📝 Publications

The considerable increase in municipal waste has become a primary global concern due to the contamination of the environment through the emission of greenhouse gases. Therefore, many OECD countries have adopted municipal waste management practices. This study is a baseline attempt to explore the long-term effect of municipal waste management along with the energy transition, environmental innovation, and environmental policy stringency on GHG emissions in ten OECD countries from 1994 to 2020. This objective is realized by using non-parametric panel quantile regression. The estimated result reveals the asymmetric effect of selected explanatory variables on GHG emissions at various quantiles. The findings show that an increase in municipal waste can increase GHGs emissions at lower quantiles, while an insignificant effect is observed at higher quantiles. Similarly, energy transition, environmental innovation, and environmental policy stringency reveal asymmetric effects across the quantiles. The findings urge OECD countries to adopt more efficient municipal waste management practices and encourage renewable energy transition and environmental innovation. Environmental policy stringency can also be instrumental in enhancing environmental sustainability.

In the context of China's rapid urbanization and pressing environmental challenges, this study evaluates the effectiveness of the New Energy Demonstration Cities initiative in fostering sustainable urban development. Employing a quasi-experimental design, the study specifically analyzed the impact of this initiative on urban green development, quantified through the metric of Green Total Factor Productivity (GTFP). Our findings reveal significant improvements in GTFP, indicating enhanced air pollution control and energy use efficiency through targeted government intervention and industrial upgrading, moderated by financial development. These results not only challenge the efficacy of broad, non-specific policies but also underscore the importance of precision in policy targeting. The study highlights how well-crafted, localized energy policies can drive substantial gains in sustainable urban growth, offering crucial insights for global policymakers and urban planners. This research extends the discourse on policy effectiveness in environmental management, suggesting pivotal areas for future investigation.

AI-Generated Content (AIGC) has recently surged in popularity, driven by its efficiency, consistent output quality, and versatile customization capabilities. While applications of image generation extend across numerous domains, research into stylized language writing system generation remains limited, particularly within the context of aesthetic enhancement. Inspired by the pictogram subset of Chinese characters, we propose ReChar, which aims to create visually appealing and culturally rich artworks that seamlessly integrate text-guided decorative elements and stylistic preferences within character structures. Additionally, we introduce ImageNet-ReChar, the first benchmark dataset designed to assess stylized character generation, with a focus on the generalization of user-defined elements. Our evaluation across multiple languages (Chinese, Japanese, English, and Latin) demonstrates ReChar’s ability to preserve original character structures while embedding decorative elements into the strokes and incorporating user-defined styles to achieve aesthetic enhancement. Our qualitative and quantitative analyses reveal that ReChar consistently outperforms existing methods.