生态保护与土壤污染防治是南京环科所的优势研究方向。信长星首先来到土壤环境管理与污染控制 重点实验室，听取发展历程介绍，详细了解农用地和建设用地土壤污染防治、地下水生态保护等研究成 果及应用情况，翻阅环科所牵头制定的各类标准规范，并就湖泊淤泥处置利用、化肥农药减量增效等问 题与大家探讨。他指出，打好净土保卫战，关键要加强源头防控。希望环科所充分发挥科研优势，针对 不同行业领域的土壤地下水污染风险管控、生态治理修复，拿出高水平的技术方案，推进精准治污、科 学治污。在新污染物暴露评估与生态效应实验室，信长星察看仪器设备，询问科研进展情况，勉励科研 人员加大前沿技术攻关力度，进一步探究新污染物的生成机制、监测手段、溯源路径、治理措施，持续 改善生态环境质量。 8月26日，省委书记信长星到生态环境部南京环境科学研究所调研。他指出，作为我国最早开展环 境保护科研的院所之一，南京环科所积淀深厚、人才济济、成果丰硕。希望南京环科所深入学习贯彻习 近平生态文明思想，聚焦前沿领域，强化科技支撑，协同推进高质量发展和高水平保护，为推进中国式 现代化江苏新实践作出更大贡献。 南京环科所研发的生物多样性智慧监测体系，涵盖了多个生物类群 ...

Core Viewpoint - The integration of AI technology in dust pollution management at construction sites is being actively explored in major cities in China, showcasing innovative solutions for environmental governance [1][2]. Group 1: Current Practices - Major cities like Shanghai and Shenzhen are implementing AI-driven systems for dust monitoring, with Shanghai using a comprehensive platform for city-wide oversight and Shenzhen enhancing its remote monitoring capabilities [1]. - These AI technologies are breaking traditional regulatory limitations and enabling data-driven, precise pollution control, providing replicable solutions for dust management [1]. Group 2: Existing Challenges - There are significant issues with the current AI monitoring systems, including a lack of comprehensive legal frameworks and technical standards, which hampers effective enforcement and data sharing [2]. - The existing systems primarily focus on basic scenarios, lacking the capability to address complex situations, and many smaller projects still rely on manual inspections due to high costs and deployment difficulties [2]. - The market for monitoring equipment is characterized by low entry barriers, leading to subpar products that compromise data integrity, and there is insufficient collaboration among various regulatory departments [2]. Group 3: Recommendations for Improvement - It is essential to enhance the regulatory and standards framework, including clarifying the legal status of AI monitoring data and establishing strict penalties for data falsification [3]. - Expanding the technical applications of AI in real-time monitoring and intelligent alerts is crucial, utilizing a combination of video surveillance, sensor networks, and IoT devices to create a comprehensive monitoring system [3]. - Implementing a robust lifecycle management for monitoring equipment, including strict market entry requirements and a collaborative maintenance model involving government, enterprises, and third parties, is necessary [4]. - Strengthening inter-departmental cooperation and public engagement through platforms for citizen reporting and targeted training for stakeholders will enhance the overall effectiveness of dust management efforts [4].

Group 1 - The State Council has initiated actions for the protection and construction of beautiful rivers and lakes, emphasizing the need for precise pollution control, scientific governance, and legal enforcement in water resource management [1] - Significant improvements in water ecological environment quality have been reported, with 92.4% of key river basins showing good water quality (Class I-III) in 2024, an increase of 0.7 percentage points year-on-year [1] - The proportion of water quality classified as inferior Class V has decreased to 0.3%, down by 0.1 percentage points compared to the previous year [1] Group 2 - The meeting highlighted the importance of a three-step approach for sustainable water pollution control, including establishing a standard system, optimizing management structures, and seeking multi-party support [2] - The need for smart management in environmental governance is emphasized, with a focus on creating a standardized asset management system for environmental infrastructure [2] - Companies are urged to enhance water pollution prevention through comprehensive lifecycle monitoring, utilizing technologies such as AI and IoT, and to bear higher costs for wastewater discharge [3]