[Effects of Green, Blue, and Blue-green Roofs on Runoff Quality].

Roofs occupy a great proportion of urban impervious surfaces, and the implementation of eco-roof construction in urban areas is beneficial to alleviate the ecological and environmental problems caused by rapid urbanization. In this study, different eco-roofs (i.e., 68.6%-90.7%, and 39.8%-54.5%, respectively. However, all the eco-roofs were sources of NO-3-N, DCr, DFe, and DNi. The blue roof was a sink of DCu (with a pollutant load reduction rate of 21.9%) and did not affect the cumulative load of PO3-4-P in runoff. However, the green roof and blue-green roof were the sources of PO3-4-P and DCu. The RQI value of the blue roof was the highest, followed by that of the blue-green roof and green roof. The RQI value of the green roof was significantly lower than that of the blue and blue-green roofs (P<0.05). These results indicated that the runoff quality of the blue roof was the best, whereas that of the green roof was the worst. Adding a storage layer to the green roofs could significantly improve the runoff quality. The results of this study provide scientific references for the selection and design of eco-roof facilities.

[Integrated Assessment of Runoff Quality from Green Roofs with Different Configurations].

Green roofs are regarded as one of the important measures for the sponge city construction. However, the comprehensive impacts of configuration factors (e.g., vegetation and substrates) on runoff quality from green roofs are not clear, which limits the promotion of green roofs. In this study, 12 green roofs with three vegetation types (i.e., Sedum lineare, Portulaca grandiflora, and non-vegetated substrates), three substrate types (i.e., local planting soil, engineered soil, and light growing medium), and two substrate depths (i.e., 10 cm and 15 cm) were set up in Beijing. During the rainy season of 2019, the rainfall characteristics, runoff volumes, and concentrations of nutrients and heavy metals of runoff from the green roofs were monitored. Based on the measured data, a runoff quality index (RQI) was developed to evaluate the comprehensive influences of configurations on runoff quality of the green roofs. The results showed that vegetation could improve runoff reduction rate and decrease the concentrations of NO3--N in runoff of green roofs. The RQIs of green roofs planted with S. linear and P. grandiflora were similar, and the evaluation results of runoff quality were better than those with non-vegetated substrates. The materials of substrates had significant influences on the runoff reduction rate and pollutant concentrations in runoff from green roofs. The green roofs with light growing medium, which had the lowest runoff reduction rates and the highest concentrations of NH4+-N, DFe, DMn, and DZn in the runoff, showed poorer runoff quality than the green roofs with local planting soil and engineered soil. The green roofs with a substrate depth of 15 cm had higher runoff reduction rates than those with 10 cm deep substrate, and the runoff quality was better than those with a substrate depth of 10 cm. The results of this study provide scientific reference for the design and integrated assessment of green roofs.

[Inter-annual Changes in Runoff Quality from Green Roofs with Different Vegetation].

As an important measure of the sponge city, green roofs have received extensive attention in recent years. To investigate the inter-annual changes in runoff quality of green roofs with different vegetation types, three green roofs with different vegetation cover (Sedum lineare, Portulaca grandiflora, and a non-vegetated control) were set up in Beijing. The influences of vegetation and monitoring period on runoff quality from the green roofs were evaluated using the plant growth characteristics and the quality of rainwater and runoff from the green roofs during the rainy season of 2017-2019. The results showed that all three green roofs were the sinks of NH4+-N, and the average mass concentration reduction rates were between 50.1% and 79.2%. However, all three green roofs were sources of PO43--P, DCr, DCu, and DNi. The green roofs covered with S. lineare and P. grandiflora were sinks of NO3--N in 2017, and the average mass concentration reduction rates were 71.4% and 99.5%, respectively, but they became sources of NO3--N in both 2018 and 2019. However, the non-vegetated control was the source of NO3--N in all three rainy seasons. Both vegetation type and length of monitoring period had significant effects on the mass concentrations of NO3--N, PO43--P, DNi, and DCu in runoff from the green roofs (P<0.05) but had no significant effects on the mass concentrations of NH4+-N and DCr in runoff from the green roofs (P>0.05). In 2017-2019, the mass concentrations of NO3--N in runoff from the non-vegetated control and the green roofs covered by S. lineare and the mass concentration of PO43--P in runoff from the green roof covered by P. grandiflora increased yearly. The mass concentrations of DNi and DCu in runoff from all three green roofs increased in 2018 but dropped in 2019. Among the green roofs with different vegetation types, the green roof covered by P. grandiflora showed better NO3--N retention capacity than that of the other green roofs but may have increased the concentrations of PO43--P, DNi, and DCu in the runoff.

Stormwater retention performance of green roofs with various configurations in different climatic zones.

Green roof stormwater retention performance is fundamentally related to design configurations and climates. Efficient tools for assessing stormwater retention performance of green roofs with various configurations in different climates are highly desirable for practical applications. In this study, a hydrological model which can be used to simulate dynamic changes in moisture content and evapotranspiration of green roofs is developed and tested (with average Nash-Sutcliffe Efficiency of 0.8197 for calibration and 0.8252 for verification) using monitoring data (2018-2019) of four green roofs with various configurations. The model is applied to simulate long-term (1970-2018) moisture content, actual evapotranspiration, and retention performance of green roofs in eight cities across different climates of China. Green roofs built with engineered soil and Portulaca grandiflora show the largest evapotranspiration and thus provide the largest stormwater retention rates (Rr), while green roofs with light growing medium and Sedum lineare show the lowest evapotranspiration and Rr. Rr of green roofs increases as climate changes from humid to arid. Green roofs at Guangzhou (humid climate) provide the lowest Rr (28% ± 3%) caused by plenty of rainfall (1827 mm), while green roofs at Urumqi (desert climate) show the lowest mean annual actual evapotranspiration (167-269 mm) but provide the largest Rr (84% ± 5%) as a result of the lowest annual rainfall (282 mm). The results highlight that stormwater retention performance of green roofs could be enhanced through configuration optimization. However, a limiting factor in improving green roofs water retention rates may be the peculiarity of local climatic conditions.