Revisiting PM_2.5 pollution along urban-rural gradient and its coupling with urbanization process, a new perspective from urban pollution island analysis

Highlights

• Urban pollution island is indexed as intensity and footprint with Gaussian model.

• Pollution island provides robust and comprehensive depiction of air pollution risk.

• Significant pollution island was found with both raising intensity and footprint.

• Urbanization acts as the key driver of urban pollution island effect in BTH region.

• Pollution island and its coupling with urbanization varied across cities and times.

Abstract

Urbanization leads to widespread urban pollution island effect. Improving our understanding of this phenomenon and its coupling with urbanization is a matter of public concern. In this study, 13 cities in the Beijing-Tianjin-Hebei region experiencing various urbanization and fine particulate matter (PM_2.5) pollution were chosen for analysis. We proposed a two-dimensional Gaussian model to index the urban pollution island effect in terms of intensity (I) and footprint (F). Then, the dynamic of I and F in the case cities during 2000–2015 and their associations with urbanization factors, including Population (POP), Built-up area (BA), and Gross domestic product (GDP), were explored. We found: (1) During 2000–2015, most of the case cities suffered continuous deteriorated urban pollution island effect in both I and F. (2) POP, BA, and GDP all contributed as effective and significant influencers, but their relative contributions to I and F are different. (3) Cities at different urbanization levels not only suffered from their own unique PM_2.5 pollution risks but were also subjected to varying causalities on urban pollution island effect. In the future, multi-index analysis of urban pollution island effect will greatly deepen the understanding of urban air pollution and provide comprehensive references for urban environmental regulation.

Introduction

The rapid urbanization process, characterized by continued population growth, energy consumption, exhaust emissions, etc., has resulted in a significant deterioration of air quality, not only locally but also regionally or globally (Boys et al., 2014; Chan and Yao, 2008; Lelieveld et al., 2015; Lim et al., 2020). For example, as the world's largest developing country that is experiencing unprecedented urbanization, China is suffering from a serious nationwide air pollution crisis (Liu et al., 2015). Since 2011, dense severe ‘haze’ events have been frequently reported in the major urbanized regions of China, e.g., Beijing-Tianjin-Hebei (BTH), Yangtze River Delta, middle reaches of the Yangtze River, etc. (Cai et al., 2017; Huang, 2015; Liu et al., 2020a). Among the numerous air pollution sources, PM_2.5 (fine particulate matter with an aerodynamic diameter ≤ 2.5 μm) has become a widely concerned indicator for the air pollution status due to its validated threat to local residential and environmental security, e.g., promoting near-ground haze weather, increasing morbidity and mortality risk of susceptible population (Fan et al., 2020; Guan et al., 2021; Han et al., 2021). As PM_2.5 has become a popular term in public opinion, understanding urban PM_2.5 pollution and its interaction mechanism thus have become one of the relevant scholarship's focuses.

To this end, previous studies have carried out a series of discussions on regional PM_2.5 pollution issue with the help of in-situ or satellite-derived data source, and most of them focused on the elaboration of mean PM_2.5 concentrations from local to global scale (Chen et al., 2018; Han et al., 2016; He et al., 2002). These efforts have greatly enriched the current knowledge of regional air pollution and convinced us that irreversible global urbanization is the important culprit of PM_2.5 pollution (Chen et al., 2018). Although these averaging concentration-based analyses can intuitively quantify and compare the air pollution status of cities or inter-cities, less attention has been paid to the pollution characteristics along the urban-rural gradient. In fact, owing to the diversity of urbanization activities, urban area and its surrounding rural area within the same city limits may exhibit significant PM_2.5 pollution variability (Huang et al., 2019). Previous study reported that PM_2.5 concentrations in urban areas were higher than the surrounding suburban and rural areas, with >10 μg/m³ in most Chinese cities (Han et al., 2014). The intensified disparity in pollutant concentration along the urban-rural gradient may induce serious disturbance on local meteorological conditions or even global physicochemical cycle and climate change (Crutzen, 2004). In addition, relatively increased PM_2.5 concentration in the urban areas often exhibit a close synergistic effect with other environmental risks (e.g., urban heat island (UHI) effect), and the integrated risks will pose negative environmental stress on residents than rural areas and are difficult to circumvent (Ulpiani, 2021). Thus, Huang (2015) termed this threat of PM_2.5 pollution risk on wider range residents as its ‘In Everyone's Backyard’ nature, which necessitates further awareness and discussion in finer dimensions and scales.

The urban pollution island effect thus is introduced to represent the differences in air pollution along the urban-rural gradient, which is in analogy with the UHI effect (Crutzen, 2004). However, current research referring to this phenomenon still focuses on using the discrete PM_2.5 concentration gap between the urban and rural areas as the key indicator, namely the intensity of urban pollution island effect (Li et al., 2018). Yet the reality is the spatial scope of the urban pollution island effect has already extended beyond the existing urban boundary (Ulpiani, 2021). This makes the perception of this effect more complex and the ordinary way of using numerical intensity cannot fully portray its continuous spatial characteristics. Considering the gradual blurring of urban boundaries with urbanization, nearby cities have developed from a scattered distribution to a cluster, and the ‘gap’ among cities furtherly shrinks in space, socio-economy, and even environmental pollution (Fang et al., 2017). Therefore, it is necessary to depict the spatial features of urban pollution island effect to comprehensively reveal both the impact magnitude and spatial extent of urban PM_2.5 pollution. Previous studies have attempted to spatialize the urban pollution island effect in terms of intensity and footprint, through statistical fitting based on concentric buffers. Their findings confirmed the existence of urban pollution island effect and further revealed its spatiotemporal characteristics in most Chinese cities (Huang et al., 2019; Zhu et al., 2020). These findings enable current scholars to understand the risk of urban PM_2.5 pollution from a new perspective, however, the relevant study remains scarce so far. In addition, due to the influence of distinct urbanization processes, PM_2.5 pollution presents significant heterogeneity across cities and times, which has been argued in both regional and global studies (Lelieveld et al., 2015; Lim et al., 2020; Wang et al., 2021a). Similar to other types of urban island effects (e.g., heat, rain, or dry/wet island), the urban pollution island should be regarded as a comprehensive urban risk entity that interacts with the population and socio-economic developments within its scope (Crutzen, 2004; Ulpiani, 2021). Previous studies on a wide range of urban environmental risks have been conducted to explore their potential relationships with the process of urbanization and gained many practical and theoretical insights into the complex mechanism of urban development on environmental degradation (Deilami et al., 2018; Fang et al., 2017; Vaden et al., 2020; Wu, 2014). However, we learn from them that there is a close but contradictory nexus between air pollution and urbanization, that is, on the one hand, the increasing entropy (waste emissions) associated with urban development will inevitably aggravate air pollution (Han et al., 2014), and on the other hand, the resources provided by urbanization is needed to improve air quality (Gao and Yuan, 2022). This complex coupling relationship is then further complicated by objective urbanization disparities in varied demographic structures & incomes, geographic locations, economic developments, etc., leading to many conflicting viewpoints in proposing solutions to the conflict (Wang et al., 2021a). Therefore, as one of the key urban environmental issues, it is essential to understand how the urban pollution island effect varies in the context of various urbanization backgrounds.

With the above expectations, this study conducted a case study to revisit the urban pollution island effect in the BTH urban agglomeration region of Northern China, where 13 cities are suffering from serious PM_2.5 pollution and various urban trajectories (He and Huang, 2018; Wang et al., 2021a). This study proposed a two-dimensional Gaussian fitting model to index the urban pollution island effect in terms of intensity and footprint, in order to characterize the spatiotemporal characteristics of PM_2.5 pollution along the urban-rural gradient (2000–2015). Several representative factors related to urbanization (i.e., population, built-up area, and GDP) were chosen for regression analysis with urban pollution island indicators. The main aims of this study were: (1) to provide detailed spatiotemporal characteristics of the urban PM_2.5 pollution for the case cities in terms of urban pollution island indicators; (2) to examine the potential coupling relationship between the urban pollution island effect and urbanization process; (3) to discuss on the main results in detail for deepening the current understanding of urban pollution island effect in the context of heterogeneous urbanization across cities and times.