AIMC Topic: Phosphorus

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Climate and traits drive bark decomposition patterns at global scale.

Nature communications
Tree bark represents a large global carbon stock, comprising 2-20 % of woody biomass, and plays a distinct role in carbon and nutrient cycling. It is poorly understood how different abiotic and biotic drivers contribute to bark decomposition globally...

Renewable Phytase Biocatalyst to Transform Biorefinery Waste Streams into Phosphorus Resources.

Environmental science & technology
Phosphorus (P) recovery is crucial for sustaining the global food supply and preventing freshwater pollution. Biorefinery waste streams have emerged as promising, yet underexplored sources for P recovery. Here, we presented a renewable and robust cel...

Human alterations to global riverine phosphorus fluxes to the ocean.

Science advances
Rivers regulate land-ocean total phosphorus (TP) fluxes critical to ecosystem health and food security, yet global dynamics remain poorly understood due to limited observations. Here, we develop a machine learning framework integrating multimodal dat...

Predicting macroelement content in legumes with machine learning.

Scientific reports
This study aims to develop accurate and efficient machine learning models to predict the concentrations of phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) in 10 legume species naturally growing in the Çamlıhemşin district of Rize prov...

River water quality forecasting: a novel LSTM-Transformer approach enhanced by multi-source data.

Environmental monitoring and assessment
Water quality prediction holds crucial importance as a fundamental technical support for efficient water resource management and strong ecological protection. In this study, aiming to meet the pressing requirement for eutrophication prevention and co...

Phosphorus removal and recovery in wastewater biological treatment from the perspective of phosphine: Current status, action mechanisms and future potential.

The Science of the total environment
This work presents a comprehensive review of phosphorus removal and resource recovery driven by phosphine (PH) in biological wastewater treatment processes, with a particular focus on PH generation. Through a bibliometric analysis using VOSviewer and...

Influence of sample size and machine learning algorithms on digital soil nutrient mapping accuracy.

Environmental monitoring and assessment
The objective of this study is to evaluate and compare the performance of different machine learning (ML) algorithms, viz., multi-layer perceptron (MLP), random forest (RF), extra trees regressor (ETR), CatBoost, and gradient boost (GB), considering ...

An artificial intelligence modeling framework based on microbial community structure prediction enhances the pollutant removal efficiency of the algae-bacteria granular sludge system.

Journal of environmental management
Algae-bacteria granular sludge (ABGS) technology is a new energy-saving and low-carbon water treatment technology based on the algae-bacteria symbiotic system. However, due to its complex internal microbial system, the regulation mechanism of ABGS is...

Exploring the contrasting lake CO fluxes and influencing variables in four large shallow subtropical lakes with different hydrological connectivity.

Journal of environmental management
Lake carbon dioxide (CO) evasion is a crucial component of global carbon cycle, yet the influence of environmental factors on CO emissions within different hydrological connectivity remains uncertain. Based on multiple machine learning methods, we in...

AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models.

Scientific reports
The integration of artificial intelligence (AI) in wastewater treatment management offers a promising approach to optimizing effluent quality predictions and enhancing operational efficiency. This study evaluates the performance of machine learning m...