**Regression Analyses of Air Pollution and Transport Based on Multiple Data Sources—A Decision Support Example for Socially Integrative City Planning**

by Mingyue Liu, Buyang Cao, Mengfan Chen, Otthein Herzog, Edna Pasher, Annemie Wyckmans and Zhiqiang Wu

In this chapter, we present a study on the inter-relationships between air pollution, transportation, industries, and social activities in a city based on multiple data sources for Tianjin. Tianjin, as one of the locations with Chinese urban living labs (living laboratories (or living labs) are spaces for co-innovation through participatory, transdisciplinary and systemic research), was selected by the TRANS URBAN EU-CHINA project as a representative city because of its size, its industries, and its importance as a main traffic node in order to verify the project results in practice. This chapter describes a top-down approach for the analysis of air pollution where multiple impact factors are taken into account. The insights gained provide evidence for decision-making to facilitate sustainable development with respect to

air pollution, which is a valuable goal in order to create more socially integrative cities, as it impacts greatly on the health and well-being of the people in affected parts of the city. The models and analyses identify some important factors impacting the air quality in Tianjin. Furthermore, a cost model for air pollution reduction provides insight into causal factors that should be taken into account while making decisions to lower air pollutants. The models may be beneficial for cities in China and elsewhere and are a contribution to evidence-based urban planning for socially integrative cities.

## **Estimating the Replication Potential of Urban Solutions for Socially Integrative Cities**

#### by Loriana Paolucci

In the previous chapters, the topic of sustainable transition toward socially integrative and sustainable cities was widely discussed and several tools and advanced methods were introduced as useful instruments to facilitate this process. All these tools are valid aids for urban planners and decision-makers in implementing specific urban solutions. Often, however, the fact that a solution is successful in a given context does not imply that it can be easily replicated in other situations and bring the same benefits. Notably, successful urban solutions in Europe, could face various difficulties when implemented in the Chinese context. Thus, a thorough analysis of the replication potential is required for the selection of the most appropriate solutions for any given city. This article illustrates a new methodology for the estimation of the replication potential of urban solutions in different contexts to support successful transition toward socially integrative cities. The novelty of this method is in the combination of quantitative data with qualitative information collected from local stakeholders, and in the assessment of five specific dimensions: socio-cultural, institutional, technological, environmental and economic (SITEE replicability method). This multi-dimensional analysis allows us to best describe and understand the complexity of the different cities' ecosystems, helping to identify the most relevant factors that may limit or facilitate replication. Cities are thus guided in the selection of those urban solutions that could be best replicated in their local context, and are widely supported in the urban planning phase and in the provision of more socially integrative initiatives. The application of SITEE to the Chinese context might have interesting implications. China's city-tier classification system can be adapted to SITEE so as to broaden and maximize the results and the impacts that can be obtained for one city, leading to the identification of a group of solutions that can be applied all the cities belonging to the same tier.
