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61,005 resultsShowing papers similar to Spatial Distribution and Geostatistical Prediction of Microplastic Abundance in a Micro-Watershed with Tropical Soils in Southeastern Brazil
ClearApplication of machine learning in assessing spatial distribution patterns of soil microplastics: a case study of the Bang Pakong Watershed, Thailand
Machine learning models were applied to predict spatial distribution patterns of microplastics in soils across a Thai watershed, identifying land use types and proximity to water bodies as key factors driving contamination levels.
Assessment of Soil Microplastics and Their Relation to Soil and Terrain Attributes Under Different Land Uses
Researchers assessed microplastic contamination in tropical soils under different land uses including forest, grassland, and agricultural areas. They found that agricultural soils had the highest microplastic concentrations, likely due to the use of plastic-based materials in farming. The study reveals how land use practices and soil characteristics influence the distribution and accumulation of microplastics in tropical environments.
Machine learning-driven analysis of soil microplastic distribution in the Bang Pakong Watershed, Thailand
Researchers used machine learning techniques to analyze the distribution and influencing factors of soil microplastic contamination in the Bang Pakong Watershed in Thailand. The study identified key environmental and land-use variables that predict microplastic occurrence, providing a data-driven approach for understanding how microplastics distribute across agricultural and urban landscapes.
Plastic Debrisin Agroecosystems: Distribution andAbundance Patterns, and Relationship with Terrain Characteristicsin Southeastern Brazil
Researchers surveyed plastic debris across forest, grassland, and agricultural land in a Southeast Brazil sub-basin, finding that agricultural areas accounted for 91.2% of total plastic waste with polypropylene, polyethylene, and PVC comprising 82.6% of polymers detected. Distribution strongly correlated with terrain characteristics, particularly slope and vegetation cover.
Effects of soil properties and land use patterns on the distribution of microplastics: A case study in southwest China
Researchers surveyed microplastic contamination in soils across different land use types in Guizhou Province, southwest China. The study found that soil properties and land use patterns significantly influence microplastic abundance and distribution, with agricultural and urban soils generally showing higher contamination levels than less intensively managed areas.
Recognizing microplastic deposits on sandy beaches by altimetric positioning, μ-Raman spectroscopy and multivariate statistical models
Researchers combined satellite positioning, Raman spectroscopy, and statistical modeling to map and characterize microplastic deposits on sandy beaches along the Sao Paulo coast in Brazil. They found that microplastic distribution was linked to beach elevation, tidal patterns, and proximity to industrial and port activities. The study introduces a replicable methodology for systematically monitoring plastic pollution on coastlines.
Identifying hot-spots for microplastic contamination in agricultural soils—a spatial modelling approach for Germany
A spatial model was developed to identify hotspots of microplastic contamination in German agricultural soils based on plastic use in farming, sewage sludge application rates, and atmospheric deposition estimates, predicting that certain intensively farmed regions accumulate substantially more plastic than previously estimated from limited field studies.
Assessing spatial variability and source identification of heavy metals in agricultural soils: A geostatistical and multivariate analysis of coastal eastern Zhejiang, China
Researchers used geostatistical and multivariate analysis techniques to assess the spatial variability and sources of five heavy metals in agricultural soils along the coast of eastern Zhejiang, China. While focused primarily on heavy metals rather than microplastics, the study provides methodology relevant to understanding pollutant distribution in coastal agricultural areas. The findings identified industrial emissions, agricultural practices, and natural geological processes as key contamination sources.
Microplastic Pollution In Agricultural Lands And Its Environmental Impact Assessed Through Remote Sensing
Researchers combined field sampling and remote sensing to assess microplastic pollution in agricultural soils across three Indian locations, finding microplastics in both surface and subsurface layers and correlating pollution levels with land use patterns detectable by satellite imagery.
Microplastic diversity, risks and soil impacts: A multi-metric assessment across land-use systems
Researchers surveyed microplastic abundance, polymer diversity, and ecological risk across seven land-use types in India's Brahmaputra Valley, finding that built-up areas had the highest particle counts while forest soils paradoxically showed the greatest polymer hazard scores due to high-risk polymers, and that land-use type shapes both the quantity and composition of soil microplastic contamination.
Microplastic Deposit Predictions on Sandy Beaches by Geotechnologies and Machine Learning Models
Researchers used satellite imagery and machine learning to predict where microplastics accumulate on sandy beaches along Brazil's northern coast. They found that beach shape, slope, and proximity to urban areas were strong predictors of microplastic deposits. The study demonstrates that geotechnology tools can help identify pollution hotspots without costly field sampling at every location.
Macro and microplastics in the soil: abundance, characterization, identification, and interactions under different land uses in an agricultural sub-basin
Researchers examined the abundance, characterization, identification, and interactions of macro- and microplastics in soils under different land uses within an agricultural sub-basin, assessing how land-use patterns influence plastic pollution distribution and potential interactions with the soil environment.
Spatial Risks ofMicroplastics in Soils and the CascadingEffects Thereof
This review mapped the spatial risks of microplastic contamination in global soils, examining how climate, land use, and human activities distribute MP pollution and analyzing cascading effects on soil ecology, carbon cycling, and ecosystem services.
A Method for the Extraction and Analysis of Microplastics from Tropical Agricultural Soils in Southeastern Brazil
Researchers developed and validated a method for extracting and analyzing microplastics from tropical agricultural soils, adapting density separation and filtration protocols to account for the high organic matter and clay content typical of tropical soil matrices.
Distribution, Environmental Risk Assessment, and Key Drivers of Microplastics in Farmland Soils Across Agricultural Zones in China
Researchers mapped the distribution and environmental risk of microplastics across a study area while identifying the key drivers of spatial variation, including land use and proximity to pollution sources. The findings provide a framework for prioritizing cleanup and management efforts in microplastic-contaminated environments.
Impact of land-use patterns on soil microplastics: Distribution characteristics and driving factors in southern China’s Pearl River Delta
A study across different land-use types in China's Pearl River Delta found that agricultural land had higher soil microplastic concentrations than urban or forested areas, with land-use history and plastic mulch film use as the dominant factors controlling MP distribution and polymer composition.
Microplastic deposits prediction on Urban Sandy Beaches: Integrating Remote Sensing, GNSS Positioning, µ-Raman Spectroscopy, and Machine Learning Models
Researchers integrated remote sensing, GNSS altimetric surveys, micro-Raman spectroscopy, and machine learning models to predict microplastic deposition patterns on urban sandy beaches along the central Sao Paulo coastline, finding MP concentrations ranging from 6 to 35 MPs/m2.
Identification of potentially contaminated areas of soil microplastic based on machine learning: A case study in Taihu Lake region, China
Researchers applied machine learning models — including random forest and support vector regression — to predict the spatial distribution of soil microplastic pollution in China's Taihu Lake region, finding that soil texture, population density, and proximity to known plastic sources were the dominant drivers, with nearly half of urban soils showing serious contamination.
Widespread microplastic pollution in mangrove soils of Todos os Santos Bay, northern Brazil
Researchers found widespread microplastic pollution in mangrove soils around Todos os Santos Bay in Brazil, detecting contamination at multiple depths and distances from the tidal area, highlighting mangroves as previously overlooked sinks for microplastic accumulation.
Microplastic deposit predictions on sandy beaches by geotechnologies and machine learning models
Researchers used geotechnologies and machine learning models to predict microplastic deposition hotspots on sandy beaches, identifying environmental and anthropogenic variables that drive spatial variation in beach microplastic accumulation.
Mapping the plastic legacy: Geospatial predictions of a microplastic inventory in a complex estuarine system using machine learning
Researchers applied machine learning techniques to develop geospatial predictions of microplastic inventory in a complex estuarine system, overcoming the limitations of coarse ocean basin models by accounting for the intricate geomorphological and hydrodynamic conditions that govern sediment-associated microplastic distribution.
The potentiality of GIS for assessing soil pollution – A review
Not relevant to microplastics — this review examines how Geographic Information Systems (GIS) can be applied to assess and map soil pollution from heavy metals, pesticides, and other contaminants, with no substantive microplastics content.
Distribution pattern and risk assessment of microplastics contamination in different agricultural systems
Researchers surveyed microplastic contamination in agricultural soils across six sites in Coimbatore, India with distinct farming practices, finding microplastics in 81% of organic matter-removed samples. The study revealed that different agronomic inputs and land management practices produce distinct microplastic contamination profiles.
Global concentrations of microplastic in soils, a review
This global review synthesized data from studies on microplastic concentrations in soils worldwide, finding contamination across diverse terrestrial environments with higher levels near urban areas and agricultural land. Terrestrial soils are estimated to contain far more microplastic than the world's oceans, making them a critical but understudied reservoir of plastic pollution.