Core Insights - The article discusses the innovative "code-based" regulatory system in Nanjing that enhances air quality management through digital solutions, transforming traditional environmental supervision methods [1][9] Group 1: Code-Based Regulatory Innovations - The "code-based" system assigns an "electronic ID" to over 5,000 activated carbon facilities, allowing for a clear management list and automatic alerts for maintenance [2][3] - The system has improved efficiency in monitoring non-road mobile machinery by creating electronic records that provide immediate access to compliance data [3] - The "code-based" series has led to a 20% reduction in on-site inspections while ensuring effective regulatory outcomes, with over 4,000 leads generated through non-site supervision in 2024 [3][8] Group 2: Enhancing Public Participation and Service - The "code-based wash" system allows restaurants to easily document and share their oil fume cleaning records, improving transparency and accountability [4][5] - The system has significantly reduced complaints from residents, with one commercial complex reporting a drop from multiple complaints per month to zero [5] - Public participation is facilitated through the "code-based" systems, enabling citizens to report issues and track resolutions, fostering a collaborative governance environment [7][8] Group 3: Multi-Department Collaboration - The "code-based" series promotes inter-departmental collaboration by breaking down data silos, allowing for more precise enforcement and identification of ineffective pollution control facilities [7][8] - The integration of various departments has led to the resolution of nearly a thousand issues since the system's implementation, enhancing overall regulatory effectiveness [7] Group 4: Achievements and Future Directions - Nanjing has achieved a PM2.5 concentration that meets national air quality standards for five consecutive years, with an 85.8% rate of good air quality days, marking the best performance on record [8] - The city plans to further optimize the "code-based" network, incorporating AI and big data analytics to strengthen ongoing air quality management efforts [9]