About this Research Topic
To promote the sustainable development of cities and societies and improve the quality of life for urban citizens, adopting a people-centric approach is crucial to achieving multiple sustainability goals such as health and well-being, carbon neutrality, and reduction of urban pollution. Holistic solutions can be attained through the integration of data acquisition, digital and/or intelligent methods, advanced technologies, and tools in the urban design process. This includes modeling and simulation, the Internet of Things (IoT), big data platforms, and artificial intelligence (AI). Strategies that promote the urban built environment and sustainable development practices should be recognized. Additionally, the focus on the use of Intelligence and big data should also be extended to tackle the social aspects of urban built environment.
This Research Topic aims to explore the status quo of urban pollution control, advanced knowledge, modeling techniques, and methods for sustainable development. It also delves into policies, urban smart control challenges, and prospects for creating sustainable cities and societies. Authors are encouraged to submit papers on the following topics:
• Intelligent sensing, modeling, and digital twin for urban environment;
• Coordinated management of urban heat island and pollution;
• Urban traffic pollution control and management;
• Blue-green infrastructure;
• Low-carbon renewal and intelligent O&M for built environment, sustainable buildings;
• Urban human mobility, spatial analysis, and city planning;
• Green and sustainable development of megacities.
Keywords: Urban heat island, Pollution in urban environment, Intelligent sensing, Low-carbon and sustainable development, Sustainable urban built environment, Safety and health
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.