Deconstructing urban green justice and well-being: a multi-group structural equation modeling analysis based on the...

Area of Science:

• Urban Planning and Environmental Justice
• Environmental Psychology
• Public Health

Background:

• Equitable access to urban green spaces is crucial for resident well-being.
• Existing research often overlooks individual activity space differences in assessing green space equity.
• This study integrates environmental justice theory with the activity space perspective.

Purpose of the Study:

• To construct and test a structural equation model linking green space quality, exposure, perceived social benefits, perceived green justice, and subjective well-being.
• To examine how these relationships differ across various activity space groups (near, mid, far).

Main Methods:

• A survey of 524 residents in Changsha, China.
• Multi-group structural equation modeling (Multi-Group SEM) was used to analyze data.
• Activity space segmentation was employed to compare path differences among groups.

Main Results:

• Green space quality positively impacts green space exposure and perceived social benefits, which in turn improve perceived green justice and subjective well-being.
• A stable core mechanism involving Green Space Quality, Green Space Exposure, and Perceived Green Justice was consistent across all activity groups.
• Green space exposure in the mid-distance group showed greater sensitivity to economic conditions.

Conclusions:

• Activity space segmentation offers a nuanced understanding of environmental justice and well-being.
• Findings support the psychological impacts of green space equity on urban residents.
• Provides empirical evidence for precision-oriented green space planning and equity-focused policy interventions.