Effect of Different Plant Communities on Fine Particle Removal in an Urban Road Greenbelt and Its Key Factors in Nanjing, China

Abstract

Determining the relationships between the structure and species of plant communities and their impact on ambient particulate matter (PM) is an important topic in city road greenbelt planning and design. The correlation between the distribution of plant communities and ambient PM concentrations in a city road greenbelt has specific spatial patterns. In this study, we selected 14 plant-community-monitoring sites on seven roads in Nanjing as research targets and monitored these roads in January 2022 for various parameters such as PM with aerodynamic diameters ≤ 10 µm (PM10) and PM with aerodynamic diameters ≤ 2.5 µm (PM2.5). We used a spatial model to analyze the relationship between the concentrations of ambient PM10 and PM2.5 and the spatial heterogeneity of plant communities. The consequences revealed that the composition and species of plant communities directly affected the concentrations of ambient PM. However, upon comparing the PM concentration patterns in the green community on the urban road, we found that the ability of the plant community structures to reduce ambient PM is in the order: trees + shrubs + grasses > trees + shrubs > trees + grasses > pure trees. Regarding the reduction in ambient PM by tree species in the plant community (conifer trees > deciduous trees > evergreen broad-leaved trees) and the result of the mixed forest abatement rate, coniferous + broad-leaved trees in mixed forests have the best reduction ability. The rates of reduction in PM10 and PM2.5 were 14.29% and 22.39%, respectively. We also found that the environmental climate indices of the road community, temperature, and traffic flow were positively correlated with ambient PM, but relative humidity was negatively correlated with ambient PM. Among them, PM2.5 and PM10 were significantly related to temperature and humidity, and the more open the green space on the road, the higher the correlation degree. PM10 is also related to light and atmospheric radiation. These characteristics of plant communities and the meteorological factors on urban roads are the foundation of urban greenery ecological services, and our research showed that the adjustment of plant communities could improve greenbelt ecological services by reducing the concentration of ambient PM.

Influence of Urban-Road Green Space Plant Configurations on NO2 Concentrations in Nanjing City during Winter

“…Nevertheless, implementing a green space structure can effectively mitigate and absorb these pollutants. Both domestic and foreign scholars have extensively researched the correlation between road green space plant configurations and pollutant concentrations [30][31][32][33][34][35][36].…”

“…Based on surveys of traffic volume on daytime and nighttime roads and the relevant literature [30][31][32][33][34][35], monitoring was conducted at three time periods: 7:00-9:00, 12:00-14:00, and 17:00-19:00, representing morning peak, off-peak, and evening peak hours, respectively [36]. In each monitoring area of the road green space, from three to four transverse observation points perpendicular to the road were established, including one observation point in the motor vehicle lane, two in the non-motor vehicle lane, and one located behind the green belt (Figure 2) [37].…”