Does pattern matter? Exploring the pathways and effects of urban green space on promoting life satisfaction through reducing air pollution

Highlights

• Green space structures cannot promote life satisfaction (LS) by reducing air pollution.

• Green space size and fragmentation are negatively related to air pollution.

• More fragmented green space distribution is associated with lower LS.

• Higher diversity of green space is related to higher LS.

• Fragmentation of green space affects LS more than diversity.

Abstract

Urban green space is widely acknowledged to promote public health through multiple pathways. However, there is limited understanding of how the spatial patterns of green space might play different roles in such a process. This study examined potential pathways through which spatial patterns of green space improved people’s life satisfaction (LS) by reducing air pollution. A partial least squares structural equation model was adopted to explore these pathways in sampled urban areas (township) of China (n = 60). Green space spatial patterns were measured using landscape metrics of size, aggregation, fragmentation, and diversity. The results did not show that green space spatial pattern promoted LS by reducing air pollution. However, green space size and fragmentation were negatively associated with air pollution (mainly PM 2.5, PM 10, and NO 2). The pattern of highly densely distributed small green spaces was related to higher LS, as was high diversity of green space type. Simply adopting a fragmented green space pattern to reduce air pollution might be simultaneously associated with reduced LS. This alerts decision-makers and planners to the potential “double-edged sword” effect of optimizing green space structures to improve air quality, which may not yield strongly favorable results due to the impacts that hinder LS.

Introduction

Air pollution, largely derived from intensive energy consumption and industrialized urbanization (Akimoto, 2003), continuously threatens public health worldwide (Landrigan, 2017). Exposure to poor air quality harms people’s well-being in multiple ways (Brunekreef and Holgate, 2002, Ekkel and de Vries, 2017, Markevych et al., 2017). Air pollution is known to be associated with psychological conditions, such as irritability, anxiety, and depression (Lu, 2020). Exposure to poor air quality also increases the chances of a low birth weight (Laurent et al., 2019) and development of several physical disorders, including respiratory and cardiovascular diseases (Brunekreef and Holgate, 2002), allergies (Mannucci et al., 2015), and diabetes (Yang et al., 2019), and it has adverse effects on the brain (Bos et al., 2014). Moreover, air pollution also causes several unfavorable social and economic outcomes, such as reduced happiness (Zheng et al., 2019) and the migration of elite professionals (Qin and Zhu, 2017). These negative outcomes of air pollution can lower the quality of life of residents and reduce their perceived life satisfaction, which has been proven through a large number of studies worldwide (Lu, 2020; Orru et al., 2016; Welsch, 2006).

Urban green space consists of vegetated outdoor spaces, such as forests, parks, private gardens, grasslands, and even street trees. All of these forms of vegetation are widely acknowledged to promote air quality (Matos et al., 2019, Nowak et al., 2018, Sun et al., 2016) and produce social and economic benefits (Kong et al., 2007; Panduro and Veie, 2013; Saphores and Li, 2012; Zhou and Parves Rana, 2012). Therefore, green space is one of the most favorable measures implemented in many countries to mitigate the negative impacts of air pollution in urban areas (Jim, 2012).

Despite the consensus that green space promotes health, limited attention has been paid to unraveling the specific underlying mechanisms and pathways of how green space enhances well-being and quality of life of residents (Markevych et al., 2017), particularly in low- and middle-income countries where air pollution is severe. Additionally, most current pathway analyses rely on quantity-based indicators to measure the green space, which provides less spatially explicit information for planning practices (Shen and Lung, 2016). The limited samples of small residential analytical units interspersed within a city also hinder its application to planning implementation (Shen and Lung, 2016) as the planning scope and scale are far from residential borders. The goal of this study was to address these gaps and expand current investigations on the pathways by which green space improves well-being by mitigating air pollution and controlling other socioeconomic and urbanicity indicators (e.g., population density (PPL) and socioeconomic levels). The three main potential contributions of this study are: (1) consideration of the impacts of the quantity, spatial pattern, and diversity of green spaces on air quality mitigation, (2) adding a national-scale case study for a large low- to middle-income country, and (3) using the smallest planning zone (the township) as the basic analytical unit to provide more direct and location-sensitive support for green-space planning.