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| 1 |
ID:
192322
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| Summary/Abstract |
As urbanization and economic development continue to accelerate, social equity issues are becoming increasingly prominent and the urban–rural income gap is an important manifestation of this. This study uses the data of urban clusters from 2010 to 2019 and focuses on the relationship between the polycentric spatial structure of urban clusters and the urban–rural income gap. The findings show that the development of urban cluster polycentricity can reduce the urban–rural income gap, and the higher the degree of polycentricity in morphology, the smaller the gap. However, the relationship between polycentric spatial structure and the urban–rural income gap is “U” shaped, indicating the need for rational planning of urban polycentric development patterns rather than simple expansion. In addition, the polycentric spatial structure of urban clusters can reduce regional disparities by promoting factor mobility and industrial structure optimization. However, this depends on the level of industrial development and infrastructure. This study highlights the importance of a balanced approach to urban development that takes into account regional disparities and issues of social equity.
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| 2 |
ID:
149868
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| Summary/Abstract |
In the field of energy conservation programs, the behavior-based method, especially the normative feedback approach, has emerged as a cost-effective solution for energy savings. However it remains doubtful whether normative feedback would generate significant energy savings in absence of financial accountability and whether the normative feedback is influenced by the proximity of the comparison groups. Here we test various normative feedback approaches at the Joint Base Andrews in Maryland, with an objective of understanding this approach. We show that the normative feedback approach can lead to 3.4% energy savings, even when residents are not billed for their electricity usage. Through an analysis of covariance, this paper evaluates the effects of different proximities of comparison and concludes that a street-level comparison level can generate the highest energy savings of 5.4%. Furthermore, this paper also explores and defines the relationship between electricity savings and physical variables including home size, unit type, neighborhood, and the variation of cooling degree days. The study contributes to the understanding of how to realizing the full potential of normative feedback approach in energy savings
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