| Literature DB >> 31159143 |
Shixin Deng1, Jiang Ma2, Lili Zhang3, Zhongkui Jia4, Luyi Ma5.
Abstract
Urban green spaces have the potential to mitigate and regulate atmospheric pollution. However, existing studies have primarily focused on the adsorption effect of different plants on atmospheric particulate matter (PM), whereas the effect of green space on PM has not been adequately addressed. In this study, the effect of different urban green space structures and configurations on PM was investigated through the 3D computational fluid dynamics (CFD) model ENVI-met by treating the green space as a whole based on field monitoring, and at the same time, the regulatory effect of green space on PM was examined by integrating information about the forest stand, PM concentration, and meteorological factors. The results show that the green space primarily affected wind speed but had no significant effect on relative humidity, temperature, or wind direction (P > 0.05). The PM concentration was significantly positively correlated with the relative humidity (P < 0.01), significantly negatively correlated with temperature (P < 0.05), but not significantly correlated with wind speed and direction (P > 0.05). Comparison with the measured values reveals that the ENVI-met model well reflected the differences in PM concentrations between different green spaces and the effect of green space on PM. In different green space structures, the uniform-type structure performed rather poorly at purifying PM, the concave-shaped structure performed the best, and the purifying effectiveness of the incremental-type and convex-shaped structure of green space was higher in the rear region than in the front region; in contrast, the degressional-type green space structure was prone to cause aggregation of the PM in the middle region. Broadleaf and broadleaf mixed forests had a better purifying effectiveness on PM than did coniferous forests, mixed coniferous forests, and coniferous broadleaf mixed forests. The above results are of great significance for urban planning and maximizing the use of urban green space resources.Entities:
Keywords: ENVI-met model; Green space configuration; Green space structure; Meteorological factor; Particulate matter
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Year: 2019 PMID: 31159143 DOI: 10.1016/j.envpol.2018.12.026
Source DB: PubMed Journal: Environ Pollut ISSN: 0269-7491 Impact factor: 8.071