Urban open space resilience evaluation of air pollution disasters based on monitoring data of national monitoring stations in Hangzhou

Abstract

Using air quality monitoring data of 2018, 2020 and 2021 from national monitoring stations in Hangzhou, the disaster cycles, with levels of ozone (O₃), fine particulate matter (PM_2.5), and coarse particulate matter (PM₁₀) were determined. The damage to human health from pollutants, which represents the loss of open space functionality, was determined by a review of the literature. Using the theory of resilience evaluation, a correlation was established between pollutant concentrations and system functions, and resilience performance curves of different types of open spaces were constructed for the urban open space pollutant disaster cycle to evaluate the resilience and related properties for open space responses to O₃, PM_2.5, and PM₁₀ pollution disasters. The results indicate that open spaces in scenic and cultural areas are more resilient to pollution than residential areas and commercial transportation residential mixed zones. All open spaces were the most robust to PM₁₀ and had the highest redundancy for O₃ and PM₁₀, while had the lowest redundancy for PM_2.5. All open spaces responded most rapidly to PM_2.5, partly because of larger scale meteorological changes in cities. All open spaces had the strongest resilience to PM₁₀ disasters, followed by O₃ disasters, with the worst resilience to PM_2.5 disasters, with a resilience index range of [0.5, 1]. The results and methods can help enhance urban resilience by bringing new ideas and broadening urban resilience theory and research. The strategy of enhancing greenery in urban open spaces was found to significantly reduce the impact of air pollution disasters, thereby reducing human health damage to users of open spaces. This is significant for enhancing urban resilience and building urban health infrastructure.

KEYWORDS:

• Resilience performance curve
• resilience index
• resilience properties
• urban open space
• environmental air monitoring data
• air pollution disaster

Data availability statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

The authors thank the Zhejiang Provincial Science and Technology Department 2021 Provincial Soft Science Research Project “Research on the Construction Mechanism of Urban Intelligent Open Space to Enhance Resilience (2021C35026)” for supporting this research.