Most existing literature supports the view that green finance has an inhibitory effect on carbon emissions.This paper re-examines the relationship between green finance and carbon emissions based on panel data from 108 prefecture-level and above cities in the Yangtze River Economic Belt from 2011 to 2022,by using a series of econometric models.Initially,a two-way fixed effects model is adopted,revealing that:The impact of green finance on carbon emissions follows an inverted U-shaped nonlinear relationship.The inhibitory effect strengthens initially and then weakens with the development of green finance,indicating diminishing marginal returns.Subsequently,a threshold effect model is employed to meticulously analyze the differentiated impact of green finance on carbon emissions under varying levels of bank competition.In regions with lower bank competition,the inhibitory effect is more pronounced,whereas in regions with intense bank competition,the emission reduction effect is relatively weaker.Further,a mediation effect model is used to confirm that artificial intelligence serves as an important channel through which green finance influences carbon emissions.Green finance indirectly reduces carbon emissions by promoting the development of artificial intelligence,validating the existence of the green finance-artificial intelligence-carbon emissions path.Finally,a spatial panel model demonstrates a significant spatial spillover effect of green finance on carbon emissions.This effect not only operates within the local region but also exerts a similar inverted U-shaped spatial influence on neighboring areas,first inhibiting and then promoting emissions,highlighting the importance of regional coordination.Based on these conclusions,the following policy recommendations are proposed:Optimizing green finance policies to coordinate the heterogeneity of carbon emissions arising from regional bank competition differences;Strengthening the application of artificial intelligence in green finance;Establishing regional cooperation mechanisms for green finance to promote coordinated emission reductions across regions.
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This This paper is to construct a systematic framework and comprehensive evaluation model for the packaging design of agri-tourism products based on the improved AHP method. Firstly, a systematic framework for the design of packaging for agri-tourism products is constructed, and a hierarchical model of the design elements is established based on the user requirements by selecting 6 criteria and 31 sub-criteria elements. Secondly, the three-scale method is used to create a judgement matrix and to derive the weights and importance ranking of the design elements. Thirdly, packaging design strategies and design solutions are generated under the guidance of sequencing. Finally the original product packaging and the generated solutions are evaluated for comparison.[1] The evaluation results shows that sensory aesthetics is the most important design element, followed by agri-tourism integration, functional attributes, and emotional needs, interactive experience and structural layout. The overall evaluation score of 3.544 for the packaging design solution generated based on the improved AHP method is higher than the original solution score of 2.331. The design example demonstrates the feasibility of improving the AHP method to effectively enhance the packaging quality of agritourism products.
电、气能源替代散煤的清洁取暖定价政策的核心是协同实现节能、减排、农户福利三重目标.我国目前在北方农村地区实施的清洁取暖价格主要为分时电价、峰谷电价和阶梯气价.通过对典型城市农户的实地调研,获得农户用能行为、需求和意愿数据,基于清洁取暖的需求价格弹性设置了多种清洁取暖用能与相应价格情景,以确定农村清洁取暖定价机制的改进策略.研究结果显示,合理划分基本生活类、改善类和奢侈类的用能需求,并在此基础上制定反映清洁能源需求价格弹性的价格,能够有效减少用能支出、改进取暖福利.同时,政府补贴在清洁取暖定价机制处于核心地位,影响清洁取暖价格政策目标的实现.为改进清洁取暖定价机制,建议对农户冬季取暖的需求和价格弹性开展充分调研,更好发挥阶梯价格的作用,并基于大气污染物持续减排的原则制定适度补贴水平.
2023 年 2 月,欧洲议会表决通过了《2035 年欧洲禁售燃油轿车和小货车零排放协议》,要求自2035年开始,在欧盟 27 国范围内全面停售新的燃油汽车和小货车.这一协议有助于推进全球交通领域碳减排进程,对欧盟"2050 碳中和"目标的实现意义重大.然而在协议通过仅半个月后,德国、意大利等国就出于保护本国燃油汽车产业利益考虑,对上述协议提出了反对意见.最终欧盟向上述国家妥协,允许他们在 2035 年以后继续销售和使用"零排放"的合成燃料汽车.德国、意大利等国的行为,为全球碳减排事业做出了错误的示范,未来可能给全球应对气候变化事业带来新的矛盾和冲突.
