Search Results (7)

Previous research has established that vegetation can significantly improve air quality. However, numerical simulations examining the purification effects of vegetation on air pollutants at the neighborhood scale remain limited, particularly regarding different neighborhood typologies. This study detailed the vegetation, buildings, and pollution emissions within neighborhoods by combining high-resolution imagery with field surveys. Then, a computational fluid dynamics model—validated through field monitoring—was used to design two scenarios to simulate and evaluate the air-purifying effects of vegetation in two typical Beijing neighborhoods. The simulation results were also well validated by the trial-and-error method compared with the computation of vegetation absorption coefficients. Findings indicated that in the Dashilar Traditional Hutong Community, vegetation contributed to reductions of 2.39% in PM_2.5 and 3.35% in CO, whereas in the east campus of Beijing University of Technology Pingleyuan, reductions were more substantial, reaching 10.07% for PM_2.5 and 8.21% for CO. The results also showed that the size and configuration of green patches directly influence PM_2.5 purification efficiency, with consolidated green areas outperforming scattered patches in particle absorption and deposition. Additionally, extensive vegetation near high-rise buildings may not yield the intended purification benefits. These findings provide a robust scientific basis for sustainable urban planning practices aimed at enhancing air quality. Full article

Monitoring the dust retention content in grassland plants around open-pit coal mines is of significant importance for environmental pollution monitoring and the development of dust control strategies. This paper focuses on the HulunBuir grassland in the Inner Mongolia Autonomous Region, China. UAV-borne hyperspectral data and measured dust retention content in plant canopies are used as data sources. The spectral response characteristics of canopy dust retention are analyzed, and four types of optimized spectral indices are constructed, including the difference index (DI), ratio index (RI), normalized difference index (NDI), and inverse difference index (IDI). The spectral index with the highest absolute value of the correlation coefficient with the canopy dust retention is selected as the feature variable for each spectral index. In addition, machine learning methods such as the partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF) methods are used to develop models for the inversion of canopy dust retention. The results show that as the dust retention content increases, the canopy reflectance in the visible wavelength initially increases and then decreases, while the reflectance in the near-infrared wavelength gradually decreases. The spectral reflectance values at different dust retention levels exhibit significant differences in the 400–420 nm, 579–698 nm, and 714–1000 nm ranges. The four types of spectral indices constructed exhibit high correlations with the canopy dust retention content, and the spectral index with the highest absolute value of the correlation coefficient is composed of near-infrared bands. The dust retention inversion model established using the RF method is more accurate than those established using the PLSR and SVM methods and yields a higher prediction accuracy. The high canopy dust retention areas are mainly distributed within 900 m of the mining area, and the dust retention gradually decreases with distance. In addition, with increasing dust retention, the fractional vegetation cover (FVC) decreases. The results of this study provide a theoretical basis and technical support for monitoring dust retention in grassland plant canopies and for dust control measures. Full article

Urban trees are known for their ability to settle fine particulate matter (PM_2.5), yet the effects of historical pollution exposure on their dust-retention capacity and stress memory remain underexplored. Therefore, we selected Euonymus japonicus Thunb. var. aurea-marginatus Hort. and Photinia × fraseri Dress, which are two common urban greening tree species in the Yangtze River Delta, a highly urbanized region in China facing severe air pollution challenges, characterized by dense urban forests, and we employed an aerosol generator to perform controlled experiments aiming to simulate PM_2.5 pollution exposure in a sealed chamber. The experiments encompassed a first pollution treatment period P1 (15 days), a recovery period R (15 days), and a second pollution treatment period P2 (15 days). The study investigates the historical impacts of pollution exposure by simulating controlled environmental conditions and assessing the morphological and physiological changes in trees. The main results are as follows: V_d of Euonymus japonicus Thunb. var. aurea-marginatus Hort. significantly decreased on the 10th day during P2 compared with that on the same day during P1, whereas V_d of Photinia × fraseri Dress significantly decreased on the 15th day. Compared with those during P1, the specific leaf area of both plants significantly decreased, the specific leaf weight significantly increased, the wax layer significantly thickened, the stomata decreased, and the content of photosynthetic pigments remained stable during P2. Furthermore, the air pollution tolerance index (APTI) generally increased during both P1 and P2. This study contributes to international knowledge by examining stress memory in urban trees and underscores the role of stress memory in enhancing plant resistance to periodic particulate pollution, offering insights into the adaptive mechanisms that can be applied globally, not just regionally. Full article

Foliar dust retention is a crucial source of uncertainty when monitoring the vegetation index using satellite remote sensing. As ground sampling conditions are limited by vegetation dust retention, separating the extinction effect of foliar dust retention from the normalized difference vegetation index (NDVI) poses a significant challenge. In this study, we conducted a correlation test between the relative change in NDVI (δNDVI, an indicator of extinction effect) retrieved by the Gaofen-4 satellite and the atmospheric PM10 concentration in different meteorological periods (before, during, and after rainfall) across 14 stations in Shenzhen City, China. The results showed a significant correlation between δNDVI and atmospheric PM10 concentration during the before-rainfall period and weaker correlations for the other periods (R = 0.680, p < 0.001, n = 63 when excluding the during- and after-rainfall data). The correlation was more significant for the stations with low NDVI values, and a coastal station had a distinct regression slope of δNDVI versus PM10 from the other stations, indicating that the extinction effect of foliar dust retention in high-NDVI and coastal areas may not be well predicted by the general δNDVI–PM10 relationship. This provides a new quantitative basis for estimating the extinction effect of foliar dust retention using PM10 data for future improvement of the accuracy of vegetation monitoring by remote sensing. Full article

In order to solve the problem of road dust pollution, an ecological dust suppressant for road surfaces has been developed using monomer, orthogonal, and optimization experiments and based on the dust raising mechanism. A humectant, hygroscopic agent, coagulant and surfactant and their concentration ranges have been determined through monomer experiment. The preliminary formula of the dust suppressant has been obtained through orthogonal experiment, with the water loss rate, moisture content rate, viscosity value, and surface tension value serving as experimental indexes. The optimal formula for the dust suppressor has been calculated through an optimization experiment, with the toxicity, moisture absorption and retention performance of plants, and the relative damage rate of plant seeds serving as experimental indexes. Based on the performance characterization of ecological road dust suppressant, the ecologically and environmentally friendly dust suppressant demonstrates fine moisture absorption and retention performance, good wind and rain erosion resistance, and no toxicity. The ecological road dust suppressant developed herein covers extensive raw material sources. It is ecologically and environmentally friendly, fit for most urban roads, and has a fine dust suppression effect. Meanwhile, it also can bring in good economic and social benefits, demonstrating its broad application prospects. Full article

In the process of urbanization in China, the problem of atmospheric suspended particulate matter pollution is becoming increasingly serious. It has been impossible to completely rely on pollution source control measures to solve this problem for a long time due to the diversity and complexity of pollution sources. Therefore, there is an urgent need to explore alternate solutions to significantly improve air quality through increasing the capacity of green space in cities as these locations can provide multiple ecosystem services. In this study, a three-dimensional classification system was created by utilizing Beijing’s urban forest as a study area. Considering the meteorological factors, change of month and time and the characteristics of the forest itself, the significance and difference of reducing the concentration of atmospheric suspended particulate matter by the forest with different vegetation structures were tested. The results showed that meteorological factors such as wind velocity, temperature, and relative humidity all had a very significant effect on the concentration of atmospheric suspended particulate matter in the conditions of this study. The concentration was highest in winter, followed by spring and autumn, and lowest in summer. The concentration in the morning was the lowest of the day, increasing in the noon and afternoon with time. It was the lowest in the closed single-layered mixed forest, and the highest in the open lawn green space. By comparing the forest with gradient areas of 0.5 ha and 3.0 ha, it was found that with the increase in the area, the green space did not necessarily show a better dust retention effect, and the vegetation structure type of the green space often had more important influence. There was a very significant correlation between vegetation structure and plant diversity (Shannon–Wiener Diversity Index and Simpson Diversity Index). Biodiversity could significantly support and strengthen urban forest ecological service functions that improve air quality. Increasing the plant species diversity could lead to lower particulate matter concentration. The research conclusions could provide theoretical and practical bases for how to select the combination of vegetation structure in the planning and design of urban forest oriented to improve air quality. Full article

Urban forests affect the filtration and absorption of airborne particulate matter, which can minimize the harmful effects to human health caused by airborne particulate pollution. Evergreen plants in urban forests play a major role in absorbing dust and purifying the air, especially in winter. Studying the spatial distribution of leaf dust and exploring the dust retention effect of evergreen shrubs are important for scientifically guiding urban forest construction and improving the living environment of cities in winter. The purpose of this study was to establish a dust inversion model by correlation analysis of spectral reflectance and the amount of dust absorption (ADA) of vegetation, using Sentinel-2 satellite remote-sensing images to obtain the dust distribution of the evergreen vegetation (mainly Euonymus japonicus Thunb.) in the Beijing urban area, and to determine the effect of the spatial pattern of E. japonicus woodland on ADA intensity. The result showed that the red band and near-infrared band are most sensitive to dust. The normalized difference phenology index (NDPI) is more suitable for building an inversion model, where the determination coefficient (R²) of the inversion model constructed by the ratio of the NDPI (R_NDPI) was 0.879. The inversion results show that the mean ADA in the enclosed area is smaller than that in semi-enclosed and open areas, and the regional distribution of high ADA in the urban area of Beijing was higher in the south with a tendency of the ADA to decrease from city center to the surrounding area. The size, shape, and percentage of landscape (PLAND) of E. japonicus woodland have a significant effect on ADA intensity. We found that, in the study area, when the PLAND of E. japonicus woodland is higher than 40%, its ADA intensity remains basically unchanged. When the vegetation coverage is fixed, the landscape shape index is negatively correlated with ADA intensity, and reduction of the overall shape complexity of forestland can enhance its dust retention effect and improve the air environment of the surrounding areas. The results of this study can be used as a reference for urban planners and landscape architects when building urban forests, providing a scientific basis for controlling and reducing air particulate pollution in Beijing’s winter and improving the living environment. Full article