With the rapid advancement of the global economy, there has been a noticeable escalation in the level of inhalable particulate matter (PM) pollution in the atmosphere. The utilization of plants has been recognized as an effective means to mitigate the escalation in the atmospheric PM concentration through the capture and retention of this particulate matter on their leaves. This research focuses on investigating the PM retention capacity of nine commonly found greening plant species in Changsha, China, located in the country’s mid-subtropical region. In this study, we employed an air aerosol generator (QRJZFSQ-II) and a portable leaf area meter (LI-3000C) to systematically evaluate the PM retention in unit leaf area for different PM values. In addition, the leaf surface structure was observed via scanning electron microscopy, and the relationship between the leaf microstructure and the retained particles was quantitatively analyzed. The results showed that (1) there were significant differences in the retention of TSP, PM₁₀, and PM_2.5 per unit leaf area among the nine greening tree species analyzed. Rosa saturata was found to have the best retention effect regarding TSP and PM_2.5, and Rhododendron simsii was found to have the best retention effect regarding PM₁₀. (2) There were significant differences in the contents of TSP and PM_2.5 per leaf area among the different tree species with different life forms (p < 0.05), with the order of retention being shrub > arbor (needle leaves) > arbor (broad leaves). (3) Coniferous plants have a deep leaf surface texture, which is conducive to capturing more particles on their leaf surface, and (4) the long stomata diameter was significantly negatively correlated with PM retention, and the stomata density was significantly positively correlated with PM retention. However, the short diameter and small area of stomata demonstrated no significant correlation with PM retention (p < 0.05). Considering the selection of suitable tree species for greening in urban air pollution control, we suggest that Osmanthus fragrans, Pseudolarix amabilis, Rosa saturata, and Rhododendron simsii be used more frequently in urban areas affected by severe air pollution.

Forest ecosystems are vital for climate mitigation, yet predicting their carbon (C) sequestration remains challenging, especially in urban-proximal regions. This study investigates the C storage dynamics across five major forest types in the Chang-Zhu-Tan Green Heart, a critical ecological buffer zone in China’s Yangtze River Mid-Reach urban agglomeration. We integrated field measurements with structural equation and random forest modeling to analyze vertical C distribution and its drivers. The results revealed that over 90% of vegetation C was stored in the tree layer, with soil C highest in evergreen broad-leaved forests (41.26 Mg C/ha). Biological factors (i.e., tree volume and biomass) primarily drove vegetation C (52–73% of variance), while non-biological factors (soil properties and micronutrients) predominantly regulated soil C. We identified distinct age-related trajectories: J-shaped accumulation in broad-leaved forests versus S-shaped patterns in coniferous and mixed forests. These findings provide a mechanistic framework for forest-type-specific management strategies to enhance C sequestration in urban-agglomeration buffer zones.

Landscape quality and the productivity of $\mathit{Rhododendron\; simsii}$ are directly related to the maintenance of ecological functions in the alpine region. The specific relationship between the spatial pattern of colour patches and the visual quality of R. simsii landscape recreational forests has been insufficiently explored. In this study, we constructed a model of the relationship between landscape colour patches and the aesthetic value of such a forest, analysing the key factors driving changes in its landscape quality. A total of 1549 participants were asked to assess 16 groups of landscape photographs. The results showed that variations in perceived aesthetic quality were stimulated by colour patch dynamics and spatial heterogeneity. Utilising structural equation modelling (SEM), we identified key indicators synergistically influencing aesthetic quality, including the area percentage, shape, and distribution of colour patches, which demonstrated strong explanatory power ($R^2$ = 0.83). The SEM also revealed that the red patch area, mean perimeter area ratio, and separation index are critical latent variables with standardised coefficients of 0.54, 0.65, and 0.62, respectively. These findings provide actionable design strategies: (1) optimising chromatic contrast through high-saturation patches, (2) controlling geometric complexity, and (3) improving spatial coherence. These results advance the theoretical framework for landscape aesthetic evaluation and offer practical guidance for landscape recreational forest management.