Leaves of urban green plants have an important role in retaining and fixing atmospheric dust particles. Euonymus japonicus is the evergreen broad-leaved shrub species with the largest acreage in Beijing, which play a major role in the retention of dust particles in winter. An urban ecosystem is one of the most frequent and intense areas of human activity. Its environment is extremely complex. In the past studies, the random and scattered urban environment was mainly used as sampling points. However, plant functional traits have a certain ecological trade-off strategy in internal or phenotypic structures due to their sensitive response and plasticity to environmental changes during long-term growth, reproduction and evolution. In the actual research process of the relationship between leaf dust retention and spectral characteristics, the important influences of water, soil, light and conservation mode of plants in different habitats were often neglected, which could not clearly explain the problem of the spectral response. Based on the law of dust particle diffusion, this study divides the high, medium and low dust concentration environment according to plant position and road surface distance, which can better avoid interference caused by light, moisture, nutrients and soil, etc. Combining the characteristics of plant functional traits, the trade-off strategy of leaf surface spectrum and leaf functional traits of Euonymus japonicus under different dust concentrations was investigated, and the relationship between its hyperspectral parameters and leaf surface dustfall was analyzed, and then a prediction model of dust retention was established. It provides an important reference for the use of hyperspectral detection of vegetation growth in urban environments. The results showed that: (1) In the environment of dust pollution, Euonymus japonicus generally showed a combination of traits with lower leaf area, lower leaf area, lower chlorophyll content, high dry matter content and high leaf thickness, which reflected the structural construction of plant leaves. The trade-off strategy between investment and return also fully illustrates the poor coercion caused by plants in order to adapt to the habitat characteristics of urban environmental pollution and adjust their own functional traits. (2) From the visible to near-infrared range (350~2 500 nm), there were four distinct reflection peaks and four major absorption valleys. In the 350~1 870 nm intervals, the spectral reflectance was generally negatively correlated with the amount of dustfall on the foliar surface. It can be seen that the spectral reflectance decrease with the number of dustfall increases. However, the variation of leaf dustfall in the 1 870~2 500 nm band was more complicated and had no obvious regularity. (3) The spectra of the 700~1 410 and 1 470~1 830 nm bands were sensitive to the response of foliar dustfall and the “red edge effect” appeared in the 680～780 nm range. A higher reflection platform appeared in the 750~1 350 nm range, which may be due to the strong absorption of the leaf moisture in this band. (4) Red edge slope, blue edge slope, yellow edge slope, and yellow edge position are very sensitive to the interference of foliar dustfall, but the red edge position and blue edge position are not obvious. Combined with the trade-off strategy of leaf functional traits, it is known that due to the long-term dust pollution environment, a special adaptation mechanism is formed. Foliar dust reduction is not sensitive to the influence of red edge position and blue edge position, showing strong Anti-interference ability. The red edge slope and the blue edge slope are negatively correlated with the foliar dustfall response, while the yellow edge slope is positively correlated with the leaf surface dustfall response. At the same time, with the increase of the amount of dust on the leaf surface, the position of the yellow edge has a significant “left shift” phenomenon. (5) In this study, foliar water content index, chlorophyll index, red edge index, normalized index, simple ratio index, and photosynthetic reflectance spectral parameters were used as independent variables, and the leaf dust retention of Euonymus japonicus was used as the dependent variable. We establish a prediction model of foliar dustfall in linear, quadratic polynomial and logarithmic forms, respectively. In all models, the quadratic polynomial prediction model based on the foliar water content index has a higher prediction accuracy for foliar dustfall (y=-1.112 3x2+0.543 9x+0.991 1, R2=0.828 9, RMSE=0.122).