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To investigate whether soda residue soil could be used as a green roof substrate, this paper setup six green roof systems with four materials (peat soil, coconut bran, perlite, and soda residue soil) mixed in different volume proportions. The effect of soda residue soil content on Sedum lineare growth and pollutant removal from the stormwater runoff was analyzed and the runoff quality index (RQI) was calculated. Results showed that the relative growth rate of S. lineare height in system B with 10% soda residue soil was about 21.5–53.2% higher than the other systems. The outflow of system B with 10% soda residue soil had the lowest mass concentration of NH4+-N and TN, which were 2.2 and 3.2 mg/L, respectively. The average repetitive rainfall retention rate of system A without soda residue soil was the lowest at 82.6%. System B had the highest RQI at about 0.71. It confirmed that soda residue soil can be a material with practical application value, and when the volume ratio of peat soil, coconut bran, perlite, and soda residue soil was 4:3:2:1, the green roof would have the best performance in regulating and purifying the initial rainwater runoff. HIGHLIGHTS The pollutant removal effects of six green roof systems with different substrate ratios on stormwater runoff were investigated.; Soda residue soil was introduced and analyzed for its effect on the operational efficiency of green roofs.; A runoff quality index (RQI) was calculated to evaluate the comprehensive influences of configurations on the runoff quality.;

The bioretention system is one of the most widely used low impact development (LID) facilities with efficient purification capacity for stormwater, and its planting design has been a hot spot for research at home and abroad. In this paper, ryegrass (Lolium perenne L.), bermuda (Cynodon dactylon Linn.), bahiagrass (Paspalum notatum Flugge), and green grass (Cynodon dactylon × C .transadlensis ‘Tifdwarf’) were chosen as plant species to construct a shallow bioretention system. The growth traits and nutrient absorption ability of four gramineous plants were analyzed. Their tolerance, enrichment, and transportation capacity were also evaluated to compare plant species and their absorptive capacity of heavy metals (Cu, Pb, and Zn). Results showed that the maximum absorption rate (Imax) ranged from 22.1 to 42.4 μg/(g·h) for P and ranged from 65.4 to 104.8 μg/(g·h) for NH4+-N; ryegrass had the strongest absorption capacity for heavy metals and the maximum removal rates of Cu, Pb, and Zn by four grasses were 78.4, 59.4, and 51.3%, respectively; the bioretention cell with ryegrass (3#) was significantly more effective in purifying than the unplanted bioretention cell (1#) during the simulated rainfall test. Overall, the system parameters were optimized to improve the technical application of gramineous plants in the bioretention system. HIGHLIGHTS Four kinds of gramineous plants were selected as plant species to construct shallow bioretention systems.; Ryegrass showed the strongest absorptive capacity for phosphorus, ammonia nitrogen, and heavy metals.; The bioretention cell with ryegrass (3#) was significantly more effective in purifying than the unplanted bioretention cell (1#) during the simulated rainfall test.;

Bioretention systems are a low-impact development (LID) measure to effectively control stormwater runoff and reduce pollutant concentrations. In this paper, three groups of bioretention cells with different filling materials (1# bioretention soil media (BSM), 2# BSM + 5% biochar, and 3# BSM +5% biochar +biological filler) were constructed to analyze the pollutant removal characteristics and microbial action under different simulated rainfall conditions. Results showed that the overall pollutant removal capacity of systems 2# and 3# was higher than that of system 1#, with system 3# having the lowest effluent concentrations of 2.71 mg/L for total nitrogen (TN) and 64.3 mg/L for chemical oxygen demand (COD). The load reduction effect for heavy metals of the three systems was ranked as 2# > 1# > 3#, and average load reduction rates were 80.3, 75.1, and 84.8% for Cu, Pb, and Zn in 2#. Microbial community analysis indicated that Proteobacteria and Firmicutes were the absolute dominant bacteria of the three bioretention systems, and the dominant genera included Bacillus, Hyphomicrobium, Micrococcaceae, and Nitrospira. In addition, the total number of denitrifying functional bacteria genera in systems 2# and 3# was increased by 1.39 and 52.1% compared to system 1#. HIGHLIGHTS The bioretention system of composite filler coupled with the water storage area was constructed for advanced treatment of stormwater runoff.; The overall pollutant removal capacity of the modified bioretention systems 2# (BSM + 5%BC) and 3# (BSM + 5%BC + BM) was improved.; The total number of denitrifying functional bacteria genera in system 3# (BSM + 5%BC + BM) was increased by 52.1% compared to system 1# (BSM).;

Summary: Air pollution is a challenge for many cities. The digital economy enhances support for environmental pollution management, while the mechanisms and scaling heterogeneity remain unclear. This study explored the contribution of digital economy development to PM2.5 concentrations control in China and driving mechanisms in different economic subregions and urban agglomerations. Results show that the spillover transfer effect on air pollution mitigation far exceeded the direct effect at different scales. At the national scale, the air pollution mitigation effect of digital economy was mainly through empowering industrial structure optimization and green technology innovation, while it also affected economic subregions and urban agglomerations through varying scenario combinations of pathways with structural optimization, green production, resource allocation, and technology innovation. Research findings provide support for cross-regional joint management strategies of digital economy and air quality and designing regionally differentiated pollution control pathways in the digital economy dimension.

Vegetation is an important strategy for mitigating heat island effects, owed to its shading and evaporative cooling functions. However, urbanization has significantly affected regional vegetation phenology and can potentially weaken the cooling potential of vegetation. Previous studies have mainly focused on national and regional vegetation phenology, but local-scale vegetation phenology and dynamic variations in built-up areas remain unclear. Therefore, this study characterized the vegetation phenology in the densely built-up area of Beijing, China over the period of 2000–2020 based on high-resolution NDVI data using Savitzky–Golay filtering and explored its spatiotemporal characteristics and drivers. The results indicate that the vegetation phenology exhibits significant spatial heterogeneity and clustering characteristics. Compared with vegetation in peripheral blocks, vegetation in central urban blocks generally has an earlier start in the growing season (SOS), later end in the growing season (EOS), and a longer growing season length (GSL). However, the overall distribution of these parameters has experienced a process of decentralization along with urbanization. In terms of drivers, vegetation phenology indicators are mainly influenced by background climate. Specifically, SOS and GSL are mainly affected by temperature (TEP), whereas EOS is mainly influenced by annual precipitation (PRE). Additionally, local environmental factors, particularly the percentage of water body (WAP), also have an impact. Notably, the local environment and background climate have a synergistic effect on vegetation phenology, which is greater than their individual effects. Overall, this study extends the current knowledge on the response of vegetation phenology to urbanization by investigating long-term vegetation phenology dynamics in dense urban areas and provides new insights into the complex interactions between vegetation phenology and built environments.