[Estimation and Critical Source Area Identification of Non-point Source Pollution Based on Improved Export Coefficient Models: A Case Study of the Upper Beiyun River Basin].

Non-point source pollution(NSP) poses a great threat to water ecosystem health. The quantitative estimation of spatial distribution characteristics and accurate identification of critical source areas(CSAs) of NSP are the basis for its efficient and accurate control. The export coefficient model(ECM) has been widely used to assess NSP, but this model should be improved because it ignores pollutant loss in transport processes. In this study, the ECM, which refines the physical transport processes of pollutants through quantifying the loss rate of pollutants in runoff, sediment, and infiltration, was improved to assess NSP and identify CSAs. The simulation accuracy among Johnes ECM, frequent ECM, and improved ECM were analyzed, and the effects of the three models on the simulation results of both spatial distribution characteristics and CSAs were explored. The study showed that:① the simulation error of the improved ECM(-6.79%) was significantly lower than that of the Johnes ECM(50.44%) and the frequent ECM(-84.01%), and this improved ECM increased the simulation accuracy of NSP. ② The spatial distribution characteristics and CSAs of NSP obtained from Johnes, frequent, and improved ECMs were significantly different, and the simulation results of improved ECM were more consistent with the spatial characteristics of NSP in the watershed. The NSP was high in the southeast and low in the northwest of the basin, and the NSP mainly came from urban and cultivated land. ③ Based on the improved ECM, the CSAs of NSP in the basin were mainly distributed in Changping, Shahe, Shigezhuang, the north of Wenquan, and the west of Malianwa Street, accounting for 6.71% of the area. This study can provide an effective tool and scientific reference for the assessment and control of NSP in data-limited regions.

Stormwater quantity and quality control performance of bioretention systems: A literature review.

Bioretention systems, as one of the most widely used modern stormwater management tools, have outstanding performance in capturing runoff, mitigating peak flow, delaying outflow occur time, and improving effluent quality. We reviewed the research of hydrologic and water quality performance of bioretention systems around the world from different perspectives, including the structure and classification of bioretention systems, the mechanisms of runoff and pollutants regulation of bioretention systems, the hydrologic and water quality performances of bioretention systems, the runoff control and water purification evaluation models of bioretention systems, as well as the influencing factors of runoff control and water purification efficiency. We proposed that future research should focus on hydrologic and water quality of bioretention systems, e.g., optimization of design configurations, revealing the mechanisms of plant action, revealing the mechanisms of microbial action, the effects of climate change on hydrologic and water quality performance, watershed/regional scale hydrologic and water quality performance, purification effect and mechanisms of emerging pollutants, maintenance methods, as well as life-cycle assessment and cost analysis. This review would provide theoretical and technical supports for research, design, construction, and maintenance of bioretention systems.

[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.

[Analysis of Spatial-Temporal Variation Characteristics of Potential Non-point Source Pollution Risks in the Upper Beiyun River Basin Using Different Weighting Methods].

Non-point source pollution has become an important factor affecting the aquatic ecological environment and human health, and the analysis of spatial-temporal variations in non-point source pollution risks is an important prerequisite for pollution control. Based on land-use and land-cover data from 1980 to 2020, the potential non-point source pollution index (PNPI) model was applied in the upper Beiyun River Basin using different weighting methods. The results showed that:① The potential risk of non-point source pollution is high in the southeast and low in the northwest of the basin. Between 1980 and 2020, the total area of extremely high-risk and high-risk non-point source pollution regions showed a decreasing trend, and the main types of land use for extremely high-risk and high-risk regions gradually evolved from paddy fields, drylands, and orchards to urban and rural residential land; ② The weighting of the land use index determined by the mean-square deviation decision, entropy, coefficient of variation, and expert scoring methods was largest among the three PNPI indices, with average weightings of 0.46, 0.53, 0.45, and 0.48, respectively. However, the weightings for runoff and distance indices determined by different weighting methods were notably different, and the proportions of regions with different levels of non-point source pollution risk also varied; ③ The exponential function method, which describes the relationship between source factors and transport factors by constructing the exponential functions of land use, runoff, and distance indices, provided results that are more consistent with the spatial distribution characteristics of non-point source pollution risk in the basin. The proportions of extremely low-risk and extremely high-risk regions are 54.22% and 6.23%, respectively. These results provide scientific reference for risk analysis and the control of non-point source pollution in this basin.

[Impacts of Vegetation on Quantity and Quality of Runoff from Green Roofs].

As a key component of green roofs, vegetation may have significant impacts on both the quantity and quality of runoff. In this study, the effects of vegetation on both the quantity and quality of runoff from green roofs are investigated through monitoring the rainfall and runoff processes of green roofs with four different types of vegetation cover (Portulaca grandiflora, Sedum lineare, Festuca elata, and a non-vegetated bed as control) during 2017. The growth characteristics of the vegetation were also monitored, and the nutrients (NH4+-N, NO3--N, NO2--N, and PO43--P) and heavy metals (Cr, Cd, Cu, and Ni) in the rainwater and runoff were measured. The results show that the average rainfall event-based runoff reduction rates for the four green roof types were 51.3%, 41.5%, 36.3%, and 33.0%, respectively. Furthermore, the runoff reduction rates of the green roof planted with Portulaca grandiflora were significantly higher than both the Festuca elata green roof and the non-vegetated bed (P<0.05). The green roofs planted with Portulaca grandiflora and Sedum lineare both acted as sinks for the nutrients. The Portulaca grandiflora green roof, which had a higher biomass, provides higher nutrient load reduction rates (59.6%, 99.9%, 82.5%, and 25.7% for NH4+-N, NO3--N, NO2--N, and PO43--P, respectively) than the Sedum lineare green roof (52.5%, 89.3%, 75.3%, and 7.8%, respectively). The Festuca elata green roof and the non-vegetation bed acted as sinks for NH4+-N and NO2--N but were sources of NO3--N and PO43--P. All four of the green roofs were sinks for DCd, with pollution load reduction rates of 19.2%, 41.5%, 38.4%, and 31.1%, respectively. However, all the green roofs acted as the sources of DCr, DCu, and DNi.

[Impacts of Vegetation on Hydrological Performances of Green Roofs Under Different Rainfall Conditions].

Vegetation is an important component of green roofs and may affect their hydrological performance through the processes of rainwater interception and evapotranspiration. Based on the rainfall-runoff observations of green roofs with four types of vegetation covers (Portulaca grandiflora, Sedum lineare, Festuca elata, and bare substrate) located in Beijing during 26 rainfall events from April to October 2017, the impacts of vegetation cover on the hydrological performance of green roofs were investigated using runoff and peak discharge reduction rates and time-delay of runoff generation and peak discharge as indices. For the 12 green roofs, there was a significantly negative correlation (P<0.01) between runoff reduction rate and rainfall event volume. For low rainfall (<10 mm), the runoff reduction rates of all the green roofs were equal or close to 100%. When the rainfall volume increased to about 30 mm, the runoff reduction rates dropped to below 70%. For the heaviest rainfall event during the observation period (81.4 mm), the runoff reduction rates of all the green roofs were less than 55%. The impacts of vegetation on the hydrological performance of green roofs changed with rainfall conditions. The differences between runoff reduction rates of green roofs with different types of vegetation cover were largest for the heavy rainfall events. For the moderate rainstorm events, the differences were slightly lower. For light rainfall events, however, no significant differences were observed among the runoff reduction rates of green roofs with different types of vegetation cover, as little runoff was generated. Vegetation cover could enhance the hydrological performance of green roofs, as the runoff and peak discharge reduction rates and time-delay of runoff generation and peak discharge of green roofs covered with vegetation were all better than those of the bare substrate for all the groups of rainfall events except the light rainfall. Vegetation-covered green roofs with P. grandiflora performed the best, as the average height and aboveground biomass per unit area of P. grandiflora were the largest.

Efficacy of HGF carried by ultrasound microbubble-cationic nano-liposomes complex for treating hepatic fibrosis in a bile duct ligation rat model, and its relationship with the diffusion-weighted MRI parameters.

Hepatic fibrosis is a major consequence of liver aggression. Finding novel ways for counteracting this damaging process, and for evaluating fibrosis with a non-invasive imaging approach, represent important therapeutic and diagnostic challenges. Hepatocyte growth factor (HGF) is an anti-fibrosis cell growth factor that induces apoptosis in activated hepatic stellate cells, reduces excessive collagen deposition, and stimulates hepatocyte regeneration. Thus, using HGF in gene therapy against liver fibrosis is an attractive approach. The aims of the present study were: (i) to explore the efficacy of treating liver fibrosis using HGF expression vector carried by a novel ultrasound microbubble delivery system; (ii) to explore the diagnostic interest of diffusion-weighted MRI (DWI-MRI) in evaluating liver fibrosis. We established a rat model of hepatic fibrosis. The rats were administered HGF linked to novel ultrasound micro-bubbles. Progression of hepatic fibrosis was evaluated by histopathology, hydroxyproline content, and DWI-MRI to determine the apparent diffusion coefficient (ADC). Our targeted gene therapy produced a significant anti-fibrosis effect, as shown by liver histology and significant reduction of hydroxyproline content. Moreover, using DWI-MRI, the b value (diffusion gradient factor) was equal to 300s/mm(2), and the ADC values significantly decreased as the severity of hepatic fibrosis increased. Using this methodology, F0-F2 could be distinguished from F3 and F4 (P<0.01). This is the first in vivo report of using an ultrasound microbubble-cationic nano-liposome complex for gene delivery. The data indicate that, this approach is efficient to counteract the fibrosis process. DWI-MRI appears a promising imaging technique for evaluating liver fibrosis.