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Abstract Urban livability has become a major policy and practice priority in many parts of the world. However, its attainment remains challenging in many cities of developing and emerging economies. The lack of data with appropriate quality, coverage, and spatial and temporal resolution often complicates both the assessment of livability in such cities and the identification of priority areas for improvement. Here we develop a framework to mobilize and synthesize open-source data to analyze spatially urban livability patterns in Shanghai. The framework brings together diverse types of open-source data including housing characteristics, population distribution, transportation networks, and points of interest to identify city areas with low livability, and thus priority areas for improvement. Such findings can provide a comprehensive overview of the residential living conditions in Shanghai, as well as useful information to urban planners and decision-makers. Furthermore, subject to data availability, the proposed method has the potential for application in other cities.

While nations have made commitments to address climate change, scholars estimate that even if these commitments are met, there remains an emissions gap between where we are and where we want to be to keep the globe under 1.5°C. Cities around the world are working to reduce this gap. Asian cities are large greenhouse gas (GHG) emitters and will be so over the next few decades. It is therefore urgent to identify ways in which the region’s cities can become more efficient and less polluting. This study is an APN research project that examines the GHG emissions at the sub-city level across 5 Asian cities (Tokyo, Beijing, Taipei, Seoul and Bangkok) as well as in New York City. The attempt is to identify potential strategies for low-carbon pathways. The research demonstrates that, in most cases, national and urban emissions are increasing, although the APN research teams identified stable emissions over the past few years in Beijing and Tokyo. However, the emissions profiles are different. Therefore, reducing emissions will require different strategies across the region’s cities. The study identifies some general policy priorities for cities based on the results of case studies.