Urban areas worldwide face escalating challenges in managing municipal solid waste (MSW) due to rapid urbanization, population growth, and changing consumption patterns. Inefficient waste management systems contribute...Urban areas worldwide face escalating challenges in managing municipal solid waste (MSW) due to rapid urbanization, population growth, and changing consumption patterns. Inefficient waste management systems contribute to environmental degradation, public health risks, and resource depletion, underscoring the need for innovative solutions. This review employing AI-driven sorting technologies in urban waste management as a transformative framework for sustainable MSW management, emphasizing waste reduction, resource recovery, and closed-loop systems. The paper synthesizes existing literature, case studies, and technological advancements to explore strategies for integrating CE principles into MSW management. Key areas of focus include the application of emerging technologies such as artificial intelligence, machine learning, and big data analytics;advancements in waste-to-resource technologies;the development of scalable and adaptable CE models tailored to diverse urban contexts;and fostering collaboration among governments, private sectors, and communities. Findings highlight the potential of CE frameworks to minimize waste generation, enhance resource efficiency, and create resilient urban systems. However, significant barriers remain, including technological, financial, and policy challenges. The review concludes by identifying future research directions and actionable recommendations for stakeholders, aiming to advance the global transition toward sustainable urban waste management.展开更多
本研究旨在建立一种高效、快速、选择性测定食品中痕量汞的方法。通过溶剂热法及后续的巯基化修饰,成功制备了一种新型巯基功能化磁性介孔二氧化硅(Thiol-functionalized Magnetic Mesoporous Silica,记为mSS@Fe_(3)O_(4))吸附剂。将该...本研究旨在建立一种高效、快速、选择性测定食品中痕量汞的方法。通过溶剂热法及后续的巯基化修饰,成功制备了一种新型巯基功能化磁性介孔二氧化硅(Thiol-functionalized Magnetic Mesoporous Silica,记为mSS@Fe_(3)O_(4))吸附剂。将该吸附剂用于磁性固相萃取(MSPE),结合原子荧光光谱法(AFS),构建了一种分析食品中痕量汞的新方法。通过X射线衍射(XRD)、傅里叶变换红外光谱(FTIR)和X射线光电子能谱(XPS)等手段对材料进行了表征,证实了巯基已成功接枝到磁性介孔二氧化硅表面。系统优化了萃取过程中的关键参数,包括样品pH值、吸附时间、吸附剂用量、洗脱液组成和上样体积。结果表明,归因于材料的介孔结构和高比表面积,吸附平衡在1 min内即可达到,实现了对Hg^(2+)的快速富集。在最优条件下,该吸附剂对Hg^(2+)的理论最大吸附容量(qm)为67.89 mg/g;在回收率保持>90%时,最大上样体积为200 mL,预浓缩因子可达200。该方法具有较宽的pH值(1~13)适用范围和优异的抗基质干扰能力。方法线性范围为0.10~4.0μg/L(相关系数r=0.9996),方法检出限(MDL)为0.012μg/kg,对空白样品进行7次平行测定的相对标准偏差(RSD)为2.4%(n=7)。通过对国家标准物质和多种实际样品(草鱼、大米等)的加标回收实验,验证了方法的准确性和可靠性,回收率在94.0%~106%。该方法集快速、高效、高选择性与高灵敏度于一体,为食品中痕量汞的常规监测提供了有力的技术支持。展开更多
文摘Urban areas worldwide face escalating challenges in managing municipal solid waste (MSW) due to rapid urbanization, population growth, and changing consumption patterns. Inefficient waste management systems contribute to environmental degradation, public health risks, and resource depletion, underscoring the need for innovative solutions. This review employing AI-driven sorting technologies in urban waste management as a transformative framework for sustainable MSW management, emphasizing waste reduction, resource recovery, and closed-loop systems. The paper synthesizes existing literature, case studies, and technological advancements to explore strategies for integrating CE principles into MSW management. Key areas of focus include the application of emerging technologies such as artificial intelligence, machine learning, and big data analytics;advancements in waste-to-resource technologies;the development of scalable and adaptable CE models tailored to diverse urban contexts;and fostering collaboration among governments, private sectors, and communities. Findings highlight the potential of CE frameworks to minimize waste generation, enhance resource efficiency, and create resilient urban systems. However, significant barriers remain, including technological, financial, and policy challenges. The review concludes by identifying future research directions and actionable recommendations for stakeholders, aiming to advance the global transition toward sustainable urban waste management.
