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Cities face global environmental challenges that exceed the capacities and mandates of current urban governance. Among those emerging challenges are the need to address global climate change, enhance public health, increase local food sourcing, eliminate environmental pollution, and convert to sustainable building practices, among others. In the present paper, we examine city-level intervention at the first and fifth of the major challenges listed above. The research is an investigation of the quantitative effects on carbon emissions (CE) of urban planning, using city-sourced big data and with a focus on local planned development. The intention is threefold: 1–to investigate how globally effective measures are possible at the local urban level; 2–to gain inference about the potential for emissions reduction by scaling up urban planning policies; 3–to return urban planning to the centre of urban decision-making using proprietary urban planning data.
With regard to global climate change, China, along with 195 other state parties, signed the Paris Agreement in the context of the UNFCCC (2016) to keep average temperature to well below 2°C increase over pre-industrial levels. In addition to the shift to renewable energy sources, a reduction of 20% is called for in CE. China’s emissions have continued to grow, however, by 1.6% in 2018 (UNEP 2019), although it is recognized that China has made significant progress toward renewable energy sources. Carbon emissions are intimately tied up with the way we build and move around the city. There has been a massive effort to reduce transport-based CE through new technologies, while green buildings have also become a trend. While these efforts are laudable, it is apparent that the size of the impact on CE of urban planning far exceeds that of the combined efforts in those other domains.
Sophisticated information technology (IT) systems have developed rapidly, especially in China. These include the monitoring of spatial dynamics in real time (Li, Qin et al., 2020), movement and user data from smartphones (Xing et al., 2020) and highly detailed information on underground infrastructure and geomorphology (Chen et al., 2020). Cities have invested in data-gathering on the city and by increasingly sophisticated means. Highly accurate planning bureau map databases include project plans integrated in a single database. These land use databases include information on building construction materials and public utilities at precise locations. While such data are essential to the efficient operations of the real estate market and city-provided services, they are also a source of data in urban planning. In addition, we have multiple sources for intra-urban travel. Most large cities conduct a periodic travel survey with a representative sample of residents over the entire city, including household information. Other censuses on employment, property values as well as new Internet-based sources, including Points of Interest (POI) provide other interesting databases for eventual policy development. The first two of these are reserved databases that do not circulate, for state security reasons or because of administrative barriers. They are, however, available to the planners in the planning bureaus, who are typically both client and guardian of the data. The data are often used for descriptive purposes in communications with decision-makers but, to the knowledge of this interested observer, have very rarely been used in analysis for policy development support. While there may be structural reasons for failure to exploit the potential of the data, the present focus is on their potential use after system reforms.