Adapt or not: A comparison of rural migrant adaptation in two cities in China.

Leading with the principle of 'people-oriented urbanization,' the adaptation of rural migrants in urban China has attracted increasing concerns from policy-makers and scholars. Today, China has proceeded to a new stage of urbanization. Many rural migrants prefer moving to cities near their home villages rather than to large cities, reflecting the changes in migration patterns and expectations of rural migrants. Although migrant adaptation has been repeatedly investigated in academia, researchers tend to address the topic in one host setting, while migrant adaptation in diverse urban settings has rarely been compared. This paper seeks to fill this research gap via a survey conducted in two cities with different urban settings in Jiangsu. The rural migrant adaptation experiences in the two cities are systematically compared. Our statistical results show that economic structure and living costs, on the one hand, and local regulations and socio-cultural environments, on the other hand, determine rural migrant adaptation experiences in different urban settings. Despite abundant employment opportunities in more-developed cities, the high living costs, working pressure, and strict institutional schemes significantly hamper rural migrant adaptation. In less-developed cities, limited employment opportunities and conservative socio-cultural environments hinder rural migrants from adapting in host societies. Our findings suggest that the governments of different cities need to tailor strategies to assist rural migrants in adapting in urban communities.

High resolution carbon emissions simulation and spatial heterogeneity analysis based on big data in Nanjing City, China.

The accurate examination of the spatial distribution of carbon emissions is critical for carbon reduction strategies. Large uncertainties still exist for previous studies which tried to simulate carbon emissions in spatial, and the resolution needs to be improved to a large extent. At a city level, this study collected various sources of big data and designed a new methodology to examine carbon emissions in Nanjing city at a high resolution of 300 m. In addition, regional differences were compared, and influence factors were analyzed. This study found, the core urban area in Nanjing presented an obvious intensity variation, but the emission intensities were much lower than in those from the peripheral region where industrial land was mainly distributed. Broad areas away from urban areas, where cropland and rural residential land were distributed, presented low carbon emission intensities. Regionally, the districts in the core urban area always presented high emission intensities. The characteristics of land usage and social-economic development were key factors in determining carbon emissions. An increase in ecological land and a decrease in developed land will help carbon reduction strategies greatly. For social and economic development, adjustments in the structure of industry and energy use efficiency improvements will play key roles in the reduction of carbon emissions.

The Built Environment and Active Travel: Evidence from Nanjing, China.

BACKGROUND: An established relationship exists between the built environment and active travel. Nevertheless, the literature examining the impacts of different components of the built environment is limited. In addition, most existing studies are based on data from cities in the U.S. and Western Europe. The situation in Chinese cities remains largely unknown. Based on data from Nanjing, China, this study explicitly examines the influences of two components of the built environment--the neighborhood form and street form--on residents' active travel. METHODS: Binary logistic regression analyses examined the effects of the neighborhood form and street form on subsistence, maintenance and discretionary travel, respectively. For each travel purpose, three models are explored: a model with only socio-demographics, a model with variables of the neighborhood form and a complete model with all variables. RESULTS: The model fit indicator, Nagelkerke's ρ², increased by 0.024 when neighborhood form variables are included and increased by 0.070 when street form variables are taken into account. A similar situation can be found in the models of maintenance activities and discretionary activities. Regarding specific variables, very limited significant impacts of the neighborhood form variables are observed, while almost all of the characteristics of the street form show significant influences on active transport. CONCLUSIONS: In Nanjing, street form factors have a more profound influence on active travel than neighborhood form factors. The focal point of the land use regulations and policy of local governments should shift from the neighborhood form to the street form to maximize the effects of policy interventions.