AIMC Topic: Soil Pollutants

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Soil geochemistry and contamination zoning in Northeastern Ghana: insights from the Bongo and Talensi districts.

Environmental geochemistry and health
Reliable geochemical baselines are largely absent for northern Ghana, limiting efforts to distinguish natural element variability from human-induced contamination. This study addresses that gap by evaluating soil geochemical compositions in the Bongo...

Interpretable artificial intelligence modeling of pre-emergence herbicide bioactivity in weakly weathered soils for optimized dose recommendations, Part I: Diclosulam.

The Science of the total environment
Conventional herbicide recommendations seldom consider soil physicochemical attributes beyond texture, overlooking key factors that govern bioavailability and environmental fate. This study presents an integrated framework for optimizing the doses of...

Perspectives on morphology, physiology, genetic polymorphism and machine learning in cucumber grafting under zinc toxicity.

BMC plant biology
BACKGROUND: Heavy metal contamination in agricultural soils disrupts plant growth and metabolism. Although zinc (Zn) is a necessary element, concentrations above 50 ppm can be toxic to plants. Grafting has emerged as a potential strategy to mitigate ...

Deep learning-driven investigation of nanoplastic impacts on soil protist behavior in soil chips.

Environmental pollution (Barking, Essex : 1987)
Nanoplastics are emerging environmental contaminants that increasingly threaten soil ecosystems, yet their effects on microbial behavior remain poorly understood. This is mainly due to the lack of experimental tools capable of directly observing micr...

Machine learning-based prediction of deep soil metal(loid) contamination in industrial areas: Role of surface environmental factors.

Environmental pollution (Barking, Essex : 1987)
Predicting the distribution of soil contamination is crucial for targeted remediation efforts and risk prevention, especially considering the high costs associated with in-situ contamination surveys. This study proposes a random forest (RF)-based app...

Quantitative inversion of soil heavy metal pollution using a GA-BP neural network model.

Environmental monitoring and assessment
With the rapid development of industrialization in China, significant economic benefits have been accompanied by varying degrees of threat to the soil environment, particularly from heavy metal pollution. The rapid quantitative inversion of heavy met...

Emerging nanosensor technologies for the rapid detection of heavy metal contaminants in agricultural soils.

Analytical methods : advancing methods and applications
The accumulation of heavy metals in agricultural soils presents a growing threat to food safety and human health. Conventional laboratory-based methods for heavy metal detection, while highly sensitive, are impractical for widespread, real-time soil ...

Integrating pollution indices, spatial interpolation, and machine learning for soil contamination analysis along the Zarqa River, Jordan.

Environmental monitoring and assessment
This study assesses soil contamination along the Zarqa River (ZR) in Jordan by integrating pollution indices, geostatistical interpolation, and machine learning models. We collected 34 soil samples from agricultural lands within the study area. Sampl...

Geographically weighted random forest fusing multi-source environmental covariates for spatial prediction of soil heavy metals.

Environmental pollution (Barking, Essex : 1987)
Efficient spatial prediction models for soil heavy metals are crucial for maintaining soil ecosystem health, promoting high-quality regional agriculture, and national food security. Traditional machine learning (ML) models often overlook spatial auto...

Assessing biodegradability potential of organic chemicals in aquatic and soil environment through classification-based machine learning models developed in accordance with OECD standards.

The Science of the total environment
Information on the biodegradation potential of organic chemicals in the ecosystem helps us analyze their persistence, bioaccumulation, and toxicity (PBT) behaviour. The environment is exposed to many chemicals from various sources, both intentionally...