English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Over the past decades rapid population growth in urban areas has promoted the development of high-density housing such as high-rise apartments. In order to properly supply water to this growing sector, it is essential to understand the determinants of its water use. However, this task has largely remained unexplored through the empirical study of water demand mainly due to the scarcity of data in this sector. Using a rich source of GIS-based urban databases in Auckland, New Zealand, this study integrated apartment water consumption, property characteristics, weather, water pricing and census microdata to overcome this issue. This study also compared high-rise apartment water use and its determinants with low-rise apartments. Through applying panel data models, the study revealed that, similar to the low-rise apartments, household size is the most important determinant of high-rise apartment water use in Auckland, where other socioeconomic factors, building features, water pricing and weather variables were not significant determinants. The study also showed that the per capita water consumption in the high-rise apartments in Auckland was higher than in the low-rise apartments, challenging the assumption underlying contemporary urban policy that densifying the central city areas can offer significant savings in water use.

Evaluating the determinants of high-rise apartment water demand through integration of water consumption, land use and demographic data