A phytoremediation approach using willow microcuttings was tested on a large experimental site spiked with Cu, Pb and Zn. The objective was to verify if this approach allows plant establishment and effective extraction of contaminants. The experimental design consisted of four blocks divided into three plots, in which treatments (salts of the three metals) were randomly applied. Each plot was also subdivided to verify the effect of adding diverse compost treatments: no compost, vegetable garden waste compost (Compost 1), food waste compost (Compost 2) and a mix of Composts 1 and 2. Willow microcuttings (Salix matsudana × alba) were scattered on the plots at a density of 60 m⁻². Nine months after the implementation, the number of stems developed, yield and concentration of metals in the aerial parts of the willows were measured. The presence of a contaminant did not affect the number of stems developed. However, the presence of Compost 1 had a significant effect on the number of stems produced as well as on the biomass. Among the three metals, Zn was the element found in highest concentration in willow tissues. An estimated minimum 300 g of Zn per hectare per year could be removed using this method.

Urban forest parks are vital ecological barriers that safeguard urban ecological security and provide essential ecosystem services. Aboveground biomass (AGB) is a key indicator for evaluating these services. This study targeted three tree species— Ligustrum lucidum , Camphora officinarum and Koelreuteria paniculata —in Haiwan National Forest Park of Shanghai, China. Based on field-measured individual tree AGB, high-density point clouds from terrestrial laser scanning (TLS), and features from UAV multispectral imagery, four machine learning models—Random Forest (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Support Vector Regression (SVR)—were developed. SHapley Additive exPlanations (SHAP) analysis was conducted to identify key predictors and quantify their importance. The results show that: (1) Data fusion of TLS and multispectral imagery significantly, improves estimation accuracy compared with single data sources, with RF consistently achieving the best performance across species (test set R ² = 0.96, 0.92, and 0.91 for L. lucidum , C. officinarum , and K. paniculata , respectively). (2) The effectiveness of data fusion varies by species: for C. officinarum and K. paniculata , fusion models outperformed TLS-only models by 2% and 5% in R ² , respectively; for L. lucidum , fusion accuracy ( R ² = 0.92) was comparable to TLS alone, both outperforming multispectral-only models. (3) SHAP analysis indicates that structural features from TLS—particularly the interaction between tree height and volume—dominate AGB estimation, contributing over 70% of the total feature importance, while spectral and vegetation index features (e.g., RE, NDVI, OSAVI) contribute about 20%. These findings demonstrate that integrating multi-source remote sensing data enables efficient and precise individual tree AGB estimation tailored to different species, providing a technical basis for intelligent monitoring of urban forests in megacity Shanghai.

The post-evaluation of ecological redevelopment is a good way of describing its achievements. In this paper, eco-engineering techniques, including hydrodynamic circulation reconstruction, water purification treatment, and aquatic ecosystem restoration, along with plant harvesting management, have been applied to reconstruct landscape water from aquaculture ponds. Both sediments and water quality were sampled and tested for basic physicochemical parameters and heavy metals. The ecological redevelopment of landscape water reconstructed from aquaculture ponds was evaluated using the single and Nemero comprehensive pollution index methods. The results demonstrate that nutrients, including organic matter and organic nitrogen and their ratio to sediments, were confirmed to be in a state of moderate pollution, while the ecological risk of heavy metal pollution was relatively low. Although the concentrations of total nitrogen and total phosphorus were significantly higher than those of other indexes, ammonia nitrogen, total nitrogen and total phosphorus, all presented obvious downward trends over time, and a majority of the water samples exhibited mild-to-moderate pollution levels. In general, this study provides a set of reference values for redeveloping water ecosystems from aquaculture ponds using eco-engineering technologies.

Post-evaluation of ecological redevelopment is a good method for its achievements. The eco-engineering technologies and achievements of landscape water reconstructed from aquaculture ponds in Shanghai Chenshan Botanical Garden have been introduced in this study. The sediments and water quality were also sampled and tested for basic physicochemical parameters and heavy metal concentration. The ecological redevelopment of landscape water reconstructed from aquaculture ponds was evaluated using the Nemero comprehensive pollution index method. The results shown that nutrients including organic matter, organic nitrogen and their ratio of sediment were found to be in a state of moderate pollution, while their ecological risk of heavy metals was low. Although total nitrogen and total phosphorus of water quality was really higher than that of other indexes, the decline trends of ammonia nitrogen, total nitrogen and total phosphorus was obvious presented over time. In general, this is a good example that redevelopment of water ecosystems from aquaculture ponds using eco-engineering technologies.

Bioaugmentation is an important measure for improving the efficiency of phytoremediation. The objective was to identify the role of exogenous plant debris with different processing and microbial agents for soil characteristics, copper bioavailability and phytoextraction. The experimental design consisted of four blocks, which were divided into 48 plots. Each plot was planted with Fraxinus chinensis and Salix matsudana × alba, which was added to plant composts, woody chips and effective microorganisms (EM) agents, using an orthogonal experimental design. The results showed that the order of bioaugmentation materials on the Cu phytoextraction of two woody species was plant composts > wood chips > EM agents. The best performance of F. chinensis was in the T15 treatment (30% plant composts + 7.5% wood chips + 40 mL·m⁻²), with phytoextraction of 33.66 mg·m⁻², as well as 4.32 mg·m⁻² in the T16 treatment (30% plant composts + 15% wood chips) of S. matsudana × alba. Cu was accumulated mainly in the roots of the two woody plants. The phytoextraction of the above-ground parts was promoted by bioaugmentation, due to the improvement in the physical soil characteristics and Cu bioavailability. The phytoextraction performance of F. chinensis was promoted by the improvement in the Cu concentration after treatments, while for S. matsudana × alba, it was the dry biomass. Thus, targeted strengthening measures should be to applied, to improve the efficiency of phytoremediation.

This study employs the AHP-entropy weight methodology and a spatial econometric regression model to evaluate the ecological sustainability and its changes between the current situation and the planning scenario at the 2024 Chengdu International Horticultural Exposition in China. The results indicate a notable shift: a reduction in areas of low and highest sustainability and significant expansion in medium levels, which spans 34.04 hm2. The transformation of village settlements, wastelands, and farmland into exhibition gardens and water bodies is shown to bolster medium-level ecological sustainability by enhancing rain and flood security and mitigating the risk of flood disasters. The development of Integrated Service areas will lead to an increase in impervious surfaces. The anticipated forest loss, along with declines in vegetation coverage, three-dimensional green volume, and vegetation carbon stock will adversely affect the highest sustainability. The study identifies a robust correlation between ecological sustainability level and quantitative indicators, with regression coefficients ranging from 0.5875 to 0.7148. This analysis provides policymakers with valuable insights and directions for the sustainable planning and development of mega-events.