Due to large specific surface area, abundant functional groups and low cost, biochar is widely used for pollutant removal. The adsorption performance of biochar is related to biochar synthesis and adsorption parameters. But the influence factor is numerous, the traditional experimental enumeration is powerless. In recent years, machine learning has been gradually employed for biochar, but there is no comprehensive review on the whole process regulation of biochar adsorbents, covering synthesis optimization and adsorption modeling. This review article systematically summarized the application of machine learning in biochar adsorbents from the perspective of all-round regulation for the first time, including the synthesis optimization and adsorption modeling of biochar adsorbents. Firstly, the overview of machine learning was introduced. Then, the latest advances of machine learning in biochar synthesis for pollutant removal were summarized, including prediction of biochar yield and physicochemical properties, optimal synthetic conditions and economic cost. And the application of machine learning in pollutant adsorption by biochar was reviewed, covering prediction of adsorption efficiency, optimization of experimental conditions and revelation of adsorption mechanism. General guidelines for the application of machine learning in whole-process optimization of biochar from synthesis to adsorption were presented. Finally, the existing problems and future perspectives of machine learning for biochar adsorbents were put forward. We hope that this review can promote the integration of machine learning and biochar, and thus light up the industrialization of biochar.
Graphical Abstract
Urban roads play a key role in sponge city construction, especially because of their drainage functions. However, efficient methods to enhance their drainage performance are still lacking. Here, we propose a new strategy to combine roads, green spaces, and the drainage system. Generally, by considering the organization of the runoff and the construction of the drainage system (including sponge city facilities) as the core of the strategy, the drainage and traffic functions were combined. This new strategy was implemented in a pilot study of road reconstruction conducted in Zhangjiagang, Suzhou, China. Steel slag was used in the structural layers to enhance the water permeability of the pavement and the removal of runoff pollutants. The combined effects of this system and of the ribbon biological retention zone, allowed achieving an average removal rate of suspended solids, a chemical oxygen demand, a removal of total nitrogen and total phosphorus of 71.60%, 78.35%, 63.93%, and 49.47%; in contrast, a traditional road could not perform as well. Furthermore, the volume control rate of the annual runoff met the construction requirements (70%). The results of the present study indicate that, combining the traditional basic functions of roads with those of landscape and drainage might be a promising strategy for sponge city construction of urban road.
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