Evaluation of Ecological Service Functions of Urban Greening Tree Species in Northern China Based on the Species-Specific Air Purification Index

Abstract

Urban forests, as an integral part of nature-based solutions (NBS), are significant contributors to improving urban air quality, delivering ecological service functions and environmental benefits to human health and well-being. Suitable urban forest management, including proper species selection, needs to be defined to efficiently reduce air pollutants in cities, with a focus on the removal ability of the main air pollutants (PM_2.5, PM₁₀, O₃, and NO₂), the ecological adaptability to O₃ and NO₂, and allergenic effects. This study ranked 73 urban greening tree species in northern Chinese cities based on their ability to maximize air quality and minimize disservices. This study proposed a novel Species-Specific Air Purification Index (S-API), which is suitable for air quality improvement for tree/shrub species. Urban managers are recommended to select species with an S-API > 1.47—that is, species that have a high removal capacity of PM_2.5, PM₁₀, O₃, and NO₂, are O₃- and NO₂-tolerant, and are non-allergenic (e.g., Castanea mollissima Blume, Ginkgo biloba L., Hibiscus syriacus L., Ilex chinensis Sims, Juniperus procumbens (Endl.) Iwata et Kusaka, Liriodendron chinense (Hemsl.) Sarg., Morus alba L., Styphnolobium japonicum (L.) Schott, Syringa oblata Lindl., and Ulmus pumila L.). The S-API of urban greening species thus represents a potentially useful metric for air pollutant risk assessment and for selecting appropriate species for urban greening in cities facing serious air pollution challenges.

1. Introduction

Rapid urbanization globally has resulted in population growth, energy consumption, and increased emissions of air pollutants [1]. Combined atmospheric pollution has become one of the most important urban concerns in China [2]. Residents are exposed to approximately 200 air pollutants in a typical urban environment [3,4]. Among these, SO₂, NO₂, CO, O₃, PM₁₀, and PM_2.5 are the pollutants currently monitored in real-time by the ambient air quality monitoring network of China. Specifically, PM_2.5, O₃, PM₁₀, and NO₂ account for 36.9%, 47.9%, 15.2%, and 0.1% of the total number of days with pollutant levels exceeding the recommended levels, respectively [5]. Ground-level O₃ concentrations in China continue to increase at a rate of 2.2–2.4 nmol/mol⁻¹ per year [6]. The peak hourly average summer O₃ concentration has exceeded 300 nmol/mol⁻¹ in densely populated areas, such as the urban agglomerations of Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Pearl River Delta, which is far beyond the critical threshold for many urban trees. This has resulted in a series of cascading negative impacts on urban trees, from impaired photosynthetic metabolism to growth inhibition and increased susceptibility to environmental stresses, thus reducing the ecological service function of urban trees [7]. Air pollution problems are more pronounced in northern Chinese cities due to their increased heating demand in winter and industrial emissions, leading to elevated concentrations of pollutants including NO₂, O₃, and PMs [8,9].

Urban plants can purify the air through physical processes, such as the retention and adhesion of air pollutants through special structures on the body surface (cilia, furrowed tissues, secretions, and so forth), and biochemical processes, such as the assimilation, absorption, and degradation of air pollutants through the stomata in plant leaves [10,11]. Different plant species have significant differences in their ability to purify air pollutants [12]. Specifically, plants retain some of the pollutants through villi-like structures on their body surface, absorb the remaining pollutants through their stomata, and transform and degrade the toxic and harmful substances through a series of detoxification processes in the apoplast and symplast [13], and then solidify and store them in various organs. This detoxification is a process of energy consumption and damage to the plant itself [14]. When the concentration of pollutants exceeds the repair capacity or the physiological limit thresholds of plants, considerable damage is caused to plants, as evidenced by leaf necrosis, premature abscission, or even premature senescence and death of the entire plant [15]. On the contrary, if the concentration of pollutants can be maintained within the repair threshold, the plants continue to remove toxic substances, forming an inherently adaptive metabolic barrier to pollutants. Therefore, plants with high repair thresholds become resistant species with strong purification capacity, whereas those with low repair thresholds are sensitive species with weak purification capacity. So, plant species with strong resistance to pollutants can effectively purify the environment [16], meet the environmental needs of residents, and improve the urban ecosystem [14].

As the “green lungs” of urban ecosystems, urban forests play a crucial role in the provision of ecosystem services [17]. They enhance the ecological resilience of cities and significantly improve the quality of life of residents. These forests effectively filter and absorb pollutants in the air, significantly reducing the concentration of pollutants such as O₃, NO₂, PM₁₀, and PM_2.5 [18]. Carbon sequestration in urban forests is important for mitigating climatic changes. Trees absorb atmospheric carbon dioxide through photosynthesis and convert it into organic matter, thus reducing the amount of greenhouse gasses in the atmosphere. Urban forests provide a more comfortable living environment for urban residents by reducing temperature and noise. They can effectively reduce the urban heat island effect through evaporative cooling and shading [19]. Moreover, they provide recreational, psychological, and esthetic benefits to residents, thereby contributing to people’s physical and mental health and well-being [20]. Nevertheless, urban forests can also have negative impacts. For example, pollen from certain trees may cause allergic reactions, affecting the health of sensitive individuals. Catkins and hairs produced by tree species may become suspended and increase the concentration of particulate matter in the air [21]. In addition, biogenic volatile organic compounds (BVOCs) released by trees may be involved in ground-level O₃ formation in the presence of light, thus adversely affecting air quality [22]. BVOCs are important precursors for near-surface ozone formation, and their emissions contribute significantly to OFP. OFP is calculated using the maximum incremental reactivity (MIR) method, which reflects the contribution of BVOCs to ozone formation [23]. Therefore, urban planners need to have a clear understanding of the extent to which urban forests contribute to air pollution and their adverse effects. Tree species that provide the greatest benefits should be screened out through scientific planning and management, and measures should be taken to mitigate their potential adverse impacts. This includes selecting tree species with low levels of pollens as allergens, rationalizing the layout of urban forests to reduce pollen dispersal, and selecting tree species with lower BVOC emissions to reduce their negative impacts on air quality [24].

Most of the studies focus on the effects of a single or a few pollutants on plants. However, plants in the actual urban environment often face the compound stress of multiple pollutants. Therefore, this study aimed (1) to quantify the removal capacity of the main air pollutants (i.e., PM_2.5, PM₁₀, O₃, and NO₂) by urban species categorized into deciduous/evergreen trees and shrubs through an extensive literature review, (2) to rank common urban species based on their ability to improve air quality and minimize disservices, and (3) to compare the air purification capabilities and air pollution conditions of tree species in the main northern Chinese cities, and provide new insights for urban greening management to maximize urban air quality in each city.

2. Materials and Methods

2.1. Determining Air Pollution Levels in Northern Chinese Cities

The Ministry of Ecology and Environment of the People’s Republic of China regularly releases the “Monthly Report on Air Quality Conditions in Chinese Cities”, covering monthly ambient air quality composite indices for 168 Chinese cities from 2014 to 2024. Utilizing this extensive dataset, a database of comprehensive air indices for 70 cities in northern China was established. The Composite Ambient Air Quality Index (I_sum) is a dimensionless index that describes the comprehensive status of urban ambient air quality, considering the pollution level of six pollutants, including SO₂, NO₂, PM₁₀, PM_2.5, CO, and O₃ [25]. The larger the value of the I_sum, the higher the comprehensive pollution level. The procedure for calculating the 2023 average I_sum for urban evaluation was as follows. (a) Calculation of the statistical concentration value of each pollutant: The monthly average concentrations of SO₂, NO₂, PM₁₀, and PM_2.5, as well as the 95th percentile of the daily average value of CO and the 90th percentile of the daily maximum 8 h value of ozone (O₃), in each city, were determined. (b) Calculation of individual indices for each pollutant: The individual index I_i for pollutant i was calculated as follows:

$$Ii={\displaystyle \frac{Ci}{Si }}$$

(1)

where Ci denotes the concentration value of pollutant i (when i is SO₂, NO₂, PM₁₀, and PM_2.5, it represents the monthly average value, and when i is CO and O₃, it represents the specific percentile concentration value); S_i denotes the annual average value of pollutant i, the secondary standard (when i is CO, it represents the secondary standard for the daily average value; when i is O₃, it represents the secondary standard for the 8 h average value). (c) Calculation of the ambient air quality composite index I_sum: We selected the maximum value from the Ii of each pollutant to determine I_sum. (d) Calculation of the 2023 mean I_sum of ambient air quality in northern cities (Table S1): Concentrations of PM, NO₂, and SO₂ are generally stable, and their impact on the environment is more related to their average concentrations. Therefore, monthly average concentrations were used in this paper to calculate these pollutants [26]. CO and O₃ concentrations fluctuate widely in the environment, and their human health effects are more correlated with peak concentrations, so it is more accurate to use percentiles to reflect their concentration levels. CO and O₃ have different concentration distributions in the environment, and therefore different percentiles are used to quantify their impacts on air quality. Concentrations of CO vary greatly throughout the day, and using the 95th percentile to assess CO concentrations better reflects the high concentration values under extreme conditions and can exclude the effects of some anomalously low values. O₃ differs from CO in that the concentration of O₃ is more affected by sunlight exposure, usually peaks in the late afternoon, and persists for a longer period. Therefore, we chose the 90th percentile to represent the 8-h maximum average concentration of O₃ [27,28]. This percentile can more comprehensively reflect the high level of exposure to O₃ throughout the day rather than just the instantaneous peak. The selection of specific percentiles for different pollutants is intended to provide a more accurate assessment of the potential hazard posed by the pollutant.

2.2. Quantification of the Removal Capacity of Air Pollutants

2.2.1. Literature Review

Approximately 209 peer-reviewed publications and technical reports spanning over the period 1994–2023 were retrieved from literature databases (China National Knowledge Infrastructure, Web of Science, Wanfang, Baidu Academic) using the terms “Cities in northern China, Air purification, Air quality, Ecosystem services, Street trees, Urban forest, Ozone, BVOC emission, Isoprene, ozone formation potential, nitrogen dioxide, pollen, catkins and hairs, adsorbing haze/dust, particulate matter, PM_2.5, PM₁₀, quantity of green” to quantify the effects of green tree species in Northern Chinese cities on the urban air quality. From each peer-reviewed publication, the following parameters were extracted: location; study duration; method; plant species; pollen allergenicity; catkin and hair allergenicity; BVOC emission potential; ozone-forming potential (OFP); leaf dust accumulation; visible injury levels; changes in physiological parameters (net photosynthetic rate, transpiration rate, and stomatal conductance) of tree species under ozone and nitrogen dioxide stress; and resistance levels to ozone and nitrogen dioxide. We evaluated the potential contribution of BVOCs to O₃ formation by introducing the OFP as an indicator. The effect of BVOCs on the atmosphere is related to their chemical reaction activities, which could be assessed by the OFP [29].

OFP = ∑MIR × Ci

(2)

where Ci denotes the determined BVOC concentrations in each tree species, MIR is defined as the maximum incremental reactivity of individual VOCs, and the specific MIR values are cited from Carter’s study [30].

2.2.2. Ranking Plant Species

A database was established based on data obtained from 209 publications that met the criteria, totaling 73 tree species belonging to 24 families and 46 genera, including 44 deciduous tree species, 12 evergreen tree species, and 17 shrub species. Of the studied species, deciduous trees accounted for 60.27%, evergreen trees accounted for 16.44%, and shrubs accounted for 23.29%.

The Species-Specific Air Purification Index (S-API) is a composite index that evaluates the ability of specific tree species to purify air pollutants. This index is calculated by assigning a weight Wi for each air pollutant i, which reflects the pollution degree of the pollutant in the city. The weighting values of major pollutants including O₃, NO₂, PM_2.5 and PM₁₀ were determined by I_i and I_sum. For non-traditional air pollutants, such as pollen and flotsam, literature studies were used to analyze and determine their weights. In addition, given the correlation between ozone formation potential (OFP) and O₃, the same weights were assigned to them as to O₃ (Table S2). At the same time, Ii represents the purification capacity of a tree species for a specific air pollutant i. The formula for calculating S-API is as follows:

S-API = ∑ (Wi × Ii)

(3)

We ranked plant species based on a multifaceted evaluation system that encapsulated their contributions to urban air quality improvement (as detailed in Table S3). A value within the range of 0–3 (0 = negligible, ±1 = low, ±2 = medium, and ±3 = high) was attributed to each plant species regarding its removal capacity for O₃, NO₂, PM_2.5, and PM₁₀; its OFP; its tolerance to O₃ and NO₂; and its allergenicity due to pollen, catkins, and hairs. However, not all pollutants have the same impact on air quality. Therefore, in order to more accurately reflect the actual impact of each pollutant on air quality, corresponding weights were assigned to each pollutant. The weighted scores of the nine indicators were then summed up to give a total score. This total score is known as the S-API, categorizing urban tree/shrub species for air quality planning from “recommended” (>1.47) to “not recommended” (<0.7). This index not only reflects the differences in air purification of different tree species but also provides an objective and scientific evaluation tool for assessing the degree of contribution of green vegetation to air quality in northern Chinese cities.

2.3. Determing Tree Species for Urban Greening in Northern Cities and Urban S-API Values

Based on official data provided by the National Forestry and Grassland Administration and various provincial forestry authorities, we compiled a comprehensive inventory of major native tree species from each province and identified the common greening tree species in northern Chinese cities (Table S4). Subsequently, using the list of common greening tree species collected from these cities and the quantified S-API data established in Section 2.2, we calculated the S-API for each city, which serves as the city’s total S-API.

$${\mathrm{S}-\mathrm{API}}_{\mathrm{city}}=\frac{\sum \mathrm{S}-\mathrm{A}\mathrm{P}\mathrm{I}\mathrm{i}}{\mathrm{n}}$$

(4)

where S-API_city is the city’s Species-Specific Air Purification Index; S-API_i is the Species-Specific Air Purification Index for tree species, where i includes all collected common greening tree species in the city; and n is the total number of tree species in the city that were included in the statistics.

3. Results

3.1. S-API Value of Common Greening Trees in Cities in Northern China

The S-API of common greening trees in cities in northern China was analyzed (Figure 1). The following evergreen tree species were considered as top-rated species for API: Pinus bungeana Zabel (1.498), Platycladus orientalis L. (1.498), Cedrus deodara (Roxb. ex D.Don) G.Don (1.569), Pinus tabuliformis Carr. (1.737), and Juniperus procumbens (Endl.) Iwata et Kusaka (1.952). Six deciduous tree species were considered as top-rated species for API: Castanea mollissima Blume (2.019), Ulmus pumila L. (1.722), Ginkgo biloba L. (1.612), Liriodendron chinense (Hemsl.) Sarg. (1.612), Malus pumila Mill. (1.603), Pyrus pyrifolia (Burm. f.) Nakai (1.545), and Morus alba L. (1.541). The following shrub species was considered as the top-rated species for the API: Hibiscus syriacus L. (1.818). On the contrary, the following nine tree species were considered as the bottom-rated species for API: Platanus orientalis L.(−0.904), Yulania denudata (Desr.) D. L. Fu (−0.818), Quercus aliena Blume (−0.761), Quercus wutaishanica Mayr (−0.761), Abies spp. (−0.761), Picea asperata Mast. (−0.761), Quercus acutissima Carruth. (−0.703), Quercus mongolica Fisch. ex Ledeb. (−0.703), and Quercus variabilis Blume (−0.703).

Figure 2 illustrates the ranking of tree species based on their positive and negative effects on air quality. The top performers, listed in order of their positive impact, are Castanea mollissima and Populus × canadensis Moench (both with a score of 2.077), Juniperus procumbens (2.067), Pinus tabuliformis (2.067), Ulmus pumila (1.837), Salix babylonica L. (1.828), Platycladus orientalis (1.828), Juniperus chinensis L. (1.828), and Hibiscus syriacus (1.818). The species with the most significant negative impacts, according to the same figure, were ranked as follows: Platanus orientalis (−0.904), Yulania denudata (−0.818), Picea asperata (−0.761), Quercus aliena Blume (−0.761), Quercus wutaishanica (−0.761), Abies spp. (−0.761), Quercus acutissima (−0.703), Quercus mongolica (−0.703), and Quercus variabilis (−0.703). The overall performance of the species, taking into account both positive and negative effects, placed Castanea mollissima (2.019) at the forefront, followed by Juniperus procumbens (1.952), Hibiscus syriacus (1.818), Pinus tabuliformis (1.737), Ulmus pumila (1.722), Ginkgo biloba (1.612), Liriodendron chinense (1.612), Malus pumila (1.603), Cedrus deodara (1.569), Pyrus pyrifolia (1.545), Morus alba (1.541), Platycladus orientalis (1.498), and Pinus bungeana (1.498).

3.2. Urban Air Pollution and S-API for Urban Tree Species in Northern China

According to urban I_sum, Zhangjiakou (2.448), Dalian (3.302), Chengde (3.364), Changchun (3.496), Beijing (3.613), Datong (3.648), Qingdao (3.674), Xinyang (3.702), Hohhot (3.725), and Harbin (3.744) were demonstrated to have relatively good air quality (Figure 3a). In contrast, 20 cities, including Linfen, Xianyang, Anyang, Weinan, Xi’an, Taiyuan, Hebi, Xinxiang, Yuncheng, Dezhou, Zibo, Xingtai, Binzhou, Liaocheng, Shijiazhuang, Handan, Zaozhuang, Lanzhou, Yangquan, and Cangzhou, performed relatively poorly and faced greater pressures in terms of air quality. Analyzed at the provincial level, Gansu (4.509), Shaanxi (4.487), Tianjin (4.474), Shandong (4.299), and Henan (4.281) provinces generally have a high I_sum, reflecting the fact that these provinces still need to further intensify their efforts in selecting and adjusting urban greening tree species.

As shown in Figure 3b, differences were found in the total S-API between cities and provinces. From the city perspective, Datong (1.406), Shuozhou (1.406), Changzhi (1.385), and Xinzhou (1.385) had relatively high S-API values, while Puyang (1.164), Jiaozuo (1.164), Xinxiang (1.164), Hebi (1.164), Anyang (1.164), Dongying (1.147), Dezhou (1.147), Huludao (1.140), and Hohhot (1.126) had relatively low S-API values.

In Figure 4, cities below the red dashed line in the S-API section are below average in urban greening’s air purification capacity. The I_sum of 4.817 and the S-API of 1.164 in Anyang, which is lower than the average S-API of 1.235 for trees in northern cities, indicate that the air pollution in Anyang is more serious and the purification ability of urban greenery is relatively low. Therefore, Anyang needs to further optimize its greening strategy, such as choosing tree species with stronger purification ability or increasing the greening coverage. The cities with lower urban S-API values (<1.180) and higher urban air pollution (>4.50) were Hebi, Xinxiang, and Dezhou in that order. On the other hand, Xinzhou has an I_sum of 4.113 and an S-API of 1.405, indicating that urban greening has a strong purification capacity for air pollution despite the city’s heavy air pollution.

4. Discussion

This study emphasized the importance of quantifying both the positive and negative combined effects of tree species and proposed a tree species evaluation and selection method based on S-API indicators, allowing for a more nuanced assessment of their potential contributions to urban air quality improvement by assigning different weights to each species’ capabilities. This approach is expected to provide guidance for urban greening management and promote improvements in urban air quality and ecological balance. While urban greening is often regarded as a cost-effective and nature-based solution for enhancing the comfort of urban environments, it also has the potential to introduce environmental problems. Therefore, the positive and negative effects of urban greening tree species need to be quantified when developing environmental countermeasures for a given city. The quantification criteria should consider the air-purifying capacity, ecological adaptability, and public health impacts of tree species to maximize the environmental benefits of urban greening. This can be achieved by optimizing the greening layout and diversifying vegetation selection.

Currently, the selection of urban greening tree species focuses on landscape esthetic value, but the research on the characteristics of tree species such as anti-pollution and pollution generation is still lacking [31]. This study established the S-API by sorting out the greening vegetation species and quantifying the air purification ability in northern Chinese cities. This index provides an important reference for developing more scientific and rational urban greening planning. The S-API evaluation system was used as a quantitative tool to rank common greening tree species in northern China according to their ability to improve air quality. The positive and negative effects of tree species were considered in this study. According to the S-API, urban planners should give preference to tree species with an S-API greater than 1.47, which are excellent in removing PM_2.5, PM₁₀, O₃ and NO₂, have better tolerance to O₃ and NO₂, and are less likely to trigger allergic reactions.

The quantitative elements of the positive effects of tree species in this study consisted of the O₃, NO₂, and PMs purification capacities of the tree species, as well as their resistance to O₃ and NO₂. Different plant species have significant differences in their dust retention capacity due to their leaf structure and morphological characteristics. Analysis of the growth habits of tree species revealed that the average S-API of evergreen tree species was 1.34, with the strongest comprehensive ability; meanwhile, the average S-API of shrubs was 1.14 and the average S-API of deciduous tree species was 1.11. The surface of evergreen plant leaves can effectively capture and retain particulate matter from the air. Then, rainwater can remove these particles from the leaves of evergreen plants, making them an effective source of particulate matter absorption throughout the year, thus providing a significant advantage in air quality improvement [32]. Some studies have shown that the efficiency of adsorption of particles by shrubs has an advantage over that of other types of plants. The blocking and absorption of PM_2.5 by typical greening shrubs in Beijing has also exhibited a certain positional advantage, with lower leaves having a greater density of particulate matter attachment than higher leaves [33]. In addition, shrubs can reduce wind speed and enhance the dust retention effect through their branch canopies [34]. Deciduous species represent the majority of common greening species in the north of China. Their obvious seasonal defoliation characteristics make their stomatal diffusion impedance small and their leaf area large, leading to the efficient absorption of gaseous pollutants [35].

Platanus spp., Quercus spp., and Pinus spp. exhibited good dust retention ability; Platanus spp., Platycladus orientalis, Juniperus chinensis L., and Pinus tabuliformis showed strong O₃ purification ability; Robinia pseudoacacia L., Ailanthus altissima (Swingle) Jacques, Koelreuteria paniculata Laxm., and Ilex chinensis Sims demonstrated strong NO₂ purification ability; Styphnolobium japonicum (L.) Schott, Populus tomentosa Carr., Robinia pseudoacacia, Ailanthus altissima, Ligustrum vicaryi Seem., Ligustrum obtusifolium Carr., and Ligustrum lucidum Ait. f. showed strong resistance to NO₂; and Hibiscus syriacus, Ginkgo biloba, Robinia pseudoacacia, Ilex chinensis, and Juniperus chinensis were more resistant to O₃. The synthesis of the data in this study showed that the following tree species demonstrated the strongest positive effects: Castanea mollissima and Populus × canadensis, Juniperus procumbens, Pinus tabuliformis, Ulmus pumila, Salix babylonica L., Platycladus orientalis, Juniperus chinensis, and Hibiscus syriacus. Wang Z X (2009) showed that Platanus spp. had a high dust retention capacity, with dust retention of up to 6.9345 g/m² [36]. In addition, coniferous species such as Pinus tabuliformis, Platycladus orientalis, and so forth had a higher dust retention capacity compared with broadleaf species [37]. Xue Wenkai et al. (2024) [38] showed that Platycladus orientalis, Juniperus chinensis, and Populus tomentosa had strong O₃ absorption and adsorption capacity and low BVOC release, identifying them as urban greening tree species with strong comprehensive resistance. These findings align with the results of this study. The negative effects of tree species quantified in this study mainly included pollen sensitization, sensitization of catkins and hairs, and OFP. The tree species producing sensitizing pollen were mainly Cupressus spp., Pinus spp., Populus spp., and Platanus spp. Catkins and hairs were mainly produced by Populus spp., Salix spp., and Platanus spp. Quercus spp., Populus spp., and Salix spp. had high OFP. Combining the data from this study showed that the following tree species had the strongest negative effects: Platanus orientalis, Yulania denudata, Picea asperata, Quercus aliena Blume, Quercus wutaishanica, Abies spp., Quercus acutissima, Quercus mongolica, and Quercus variabilis. Combining the positive and negative aspects, Castanea mollissima, Juniperus procumbens, Hibiscus syriacus, Pinus tabuliformis, Ulmus pumila, Ginkgo biloba, Liriodendron chinense, Malus pumila, Cedrus deodara, Pyrus pyrifolia, Morus alba, Platycladus orientalis, and Pinus bungeana scored the highest, making them the preferred choices in urban greening.

Air pollution in the north of China is dominated by particulate matter (PM_2.5 and PM₁₀) and gaseous pollutants (SO₂, NO₂, and O₃). In terms of geographic location, SO₂, NO₂, PMs, and O₃ all have an increasing trend in the north than in the south of China. In terms of particulate matter, the annual average concentration of PM_2.5 in the north of China was 62.28 μg/m³, which was 12.62 μg/m³ higher than that in the south, and the annual average concentration of PM₁₀ in the north was 115.98 μg/m³, which was 36.34 μg/m³ higher than that in the south [39]. O₃ is the major pollutant affecting the air quality in Chinese cities after PM_2.5 [6]. Ozone pollution is associated with a variety of precursors, including volatile organic compounds (VOCs) and nitrogen oxides (NO_x) [40]. VOCs are also an important component of air pollution in northern cities. The hotspots of O₃ are concentrated in the urban agglomerations of Beijing–Tianjin–Hebei, the Yangtze River Delta, the Pearl River Delta, the Shandong Peninsula urban agglomeration, the Central Plains urban agglomeration, and the urban agglomeration in the middle reaches of the Yangtze River [41]. The hotspots of NO₂ are concentrated in the urban agglomerations of Luzhong, Ji’nan, and the Pearl River Delta. In contrast, the hotspots of PMs are concentrated in the economic zones of Beijing–Tianjin–Hebei, the Yangtze River Delta, the Huaihai Sea, and the coastal areas of southern China [14]. Given the current air quality challenges faced by northern cities, tree species with superior comprehensive efficacy should be selected for planting, taking into account the differences in urban greening and protection needs between the Yangtze River Delta and Beijing–Tianjin–Hebei regions. The benefits of urban forests in resisting, purifying, and adsorbing air pollutants can be maximized by optimizing the selection of tree species. Also, the focus should be on the rational layout of greening space and vegetation diversity.

In practical urban greening initiatives, the S-API, while a significant reference metric, is not the exclusive determinant for selection. The choice of tree species should also take into account detailed considerations of specific environmental conditions to optimize ecological and social benefits. In certain environments, tree species with modest S-API indices may demonstrate notable advantages due to their distinctive ecological functions. For example, in urban settings where O₃ and NO₂ levels are comparatively low but PM_2.5 and PM₁₀ levels are elevated, it may be more effective to enhance local air quality by selecting tree species that have a strong capacity to adsorb PMs but do not necessarily have a high S-API. Moreover, the allergenicity of tree pollen and hairs is an essential consideration in urban greening endeavors. Tree species with low allergenicity are well-suited for planting in areas with high human traffic, such as parks, residential neighborhoods, and along streets, to minimize potential adverse effects on public health. Conversely, tree species with higher allergenicity should be strategically excluded from densely populated areas to mitigate the prevalence of allergic conditions.

Baldauf (2017) has provided valuable insights for the refinement of the S-API by highlighting the significance of roadside vegetation design characteristics in enhancing the air quality near roads [42]. Key attributes such as the height, density, and coverage of vegetation play a crucial role. It has been observed that low, dense vegetation is more effective in improving air quality within urban street canyons, whereas tall trees may hinder air circulation and lead to the accumulation of pollutants. Abhijith et al. (2017) further demonstrated the potential of green infrastructure in mitigating traffic-related pollution. The selection and arrangement of vegetation are critical to maximizing its air-purifying capabilities [43]. Therefore, future research on the S-API should consider the physical characteristics of vegetation, such as height and density, as well as their interactions with the surrounding built environment. This approach will ensure that the chosen plants can provide the greatest air purification benefits in specific urban settings. Refining the S-API will not only assess the purification capacity of individual plant species but also offer a more comprehensive framework for the selection and layout of urban greenery. This will ultimately lead to improved air quality in various road environments.

In the cities we have studied, the selection of urban greening tree species has not been entirely based on their ability to purify the air, and the current selection process of urban greening tree species may not fully consider their specific impact on air quality. Therefore, we suggest that future urban greening plans should refer more to the S-API and choose tree species that can effectively improve air quality. This will not only help to enhance the ecological benefits of urban greening but also provide city planners and decision-makers with a more accurate tool for air quality assessment. By scientifically selecting tree species, the role of urban greening in improving the environment and enhancing the quality of life for residents can be made more effective.

Combining the comprehensive ambient air quality conditions and urban S-APIs of northern Chinese cities, the optimization of tree species in Anyang, Hebi, Xinxiang, Zibo, Liaocheng, Zaozhuang, and Lanzhou cities has much space for improvement. Given the air quality challenges faced by these cities, priority should be given to selecting tree species with strong air-purifying abilities to accelerate air quality improvement. Therefore, cities should prioritize the planting of tree species with high S-API in highly polluted and densely populated areas and avoid planting O₃- and NO₂-sensitive tree species. Additionally, tree species with low emissions of pollen, catkins and hairs, and VOCs should be selected [10,44]. The proposed S-API in this study needs further improvement and validation in the future, including the incorporation of additional criteria such as tree biological traits, maintenance cost, and adaptability to urban conditions. Taking these factors into account, urban planners and landscape architects use flexible strategies to select and configure tree species according to the level of pollutants, the health of the population, and the need for ecological balance. This will not only help to improve the overall quality of urban greening but also ensure that greening efforts better serve the well-being of urban residents and the health of the urban ecology.

5. Conclusions

Urban forests could be considered as a cost-effective and nature-based approach by policymakers, especially in urban areas where climatic change is expected to be more pronounced. Planting tree species with a high S-API can be a viable strategy to improve the air quality and citizens’ well-being. The following tree species, known for their strong air purification capacity, are recommended for planting: Castanea mollissima, Juniperus procumbens, Hibiscus syriacus, Pinus tabuliformis, Ulmus pumila, Ginkgo biloba, Liriodendron chinense, Malus pumila, Cedrus deodara, Pyrus pyrifolia, Morus alba, Platycladus orientalis, and Pinus bungeana. The benefits of trees need to be included as key strategies for improving air quality and mitigating climatic change effects in urban areas. These benefits can also address the needs of society, including recreational, cultural, and esthetic value.