Clean-Up of Heavy Metals from Contaminated Soil by Phytoremediation: A Multidisciplinary and Eco-Friendly Approach

Toxics, Год журнала: 2023, Номер 11(5), С. 422 - 422

Опубликована: Май 2, 2023

Pollution from heavy metals is one of the significant environmental concerns facing world today. Human activities, such as mining, farming, and manufacturing plant operations, can allow them access to environment. Heavy polluting soil harm crops, change food chain, endanger human health. Thus, overarching goal for humans environment should be avoidance contamination by metals. persistently present in absorbed tissues, enter biosphere, accumulate trophic levels chain. The removal contaminated accomplished using various physical, synthetic, natural remediation techniques (both situ ex situ). most controllable (affordable eco-friendly) method among these phytoremediation. metal defilements phytoremediation techniques, including phytoextraction, phytovolatilization, phytostabilization, phytofiltration. bioavailability biomass plants are two main factors affecting how effectively works. focus phytomining on new hyperaccumulators with high efficiency. Subsequently, this study comprehensively examines different frameworks biotechnological available eliminating according guidelines, underscoring difficulties limitations its potential application clean-up other harmful pollutants. Additionally, we share in-depth experience safe removing used phytoremediation—a factor frequently overlooked when choosing remove conditions.

Язык: Английский

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Remote sensing of soil degradation: Progress and perspective

International Soil and Water Conservation Research, Год журнала: 2023, Номер 11(3), С. 429 - 454

Опубликована: Март 15, 2023

Soils constitute one of the most critical natural resources and maintaining their health is vital for agricultural development ecological sustainability, providing many essential ecosystem services. Driven by climatic variations anthropogenic activities, soil degradation has become a global issue that seriously threatens environment food security. Remote sensing (RS) technologies have been widely used to investigate as it highly efficient, time-saving, broad-scope. This review encompasses recent advances state-of-the-art ground, proximal, novel RS techniques in degradation-related studies. We reviewed RS-related indicators could be monitoring properties. The direct (mineral composition, organic matter, surface roughness, moisture content soil) indirect proxies (vegetation condition land use/land cover change) evaluating were comprehensively summarized. results suggest these above are effective degradation, however, no system established date. also discussed RS's mechanisms, data, methods identifying specific phenomena (e.g., erosion, salinization, desertification, contamination). investigated potential relations between Sustainable Development Goals (SDGs) challenges prospective use assessing degradation. To further advance optimize technology, analysis retrieval methods, we identify future research needs directions: (1) multi-scale degradation; (2) availability data; (3) process modelling prediction; (4) shared dataset; (5) decision support systems; (6) rehabilitation degraded resource contribution technology. Because difficult monitor or measure all properties large scale, remotely sensed characterization related particularly important. Although not silver bullet, provides unique benefits studies from regional scales.

Язык: Английский

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Phytoremediation of potentially toxic elements (PTEs) contaminated soils using alfalfa (Medicago sativa L.): A comprehensive review

Chemosphere, Год журнала: 2022, Номер 293, С. 133577 - 133577

Опубликована: Янв. 8, 2022

Язык: Английский

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Monitoring of soil heavy metals based on hyperspectral remote sensing: A review

Earth-Science Reviews, Год журнала: 2024, Номер 254, С. 104814 - 104814

Опубликована: Май 15, 2024

Язык: Английский

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The Effect of Drought on Vegetation Gross Primary Productivity under Different Vegetation Types across China from 2001 to 2020

Remote Sensing, Год журнала: 2022, Номер 14(18), С. 4658 - 4658

Опубликована: Сен. 18, 2022

Climate change has exacerbated the frequency and severity of droughts worldwide. Evaluating response gross primary productivity (GPP) to drought is thus beneficial improving our understanding impact on carbon cycle balance. Although many studies have investigated relationship between vegetation dry/wet conditions, capability different indices assessing influence water deficit not well understood. Moreover, few consider effects with a focus periods drought. Here, we spatial-temporal patterns GPP, standardized precipitation evapotranspiration index (SPEI), vapor pressure (VPD) in China from 2001 2020 examined GPP deficit/drought for types. The results revealed that SPEI were positively correlated over approximately 70.7% total area, VPD was negatively about 66.2% domain. Furthermore, more affected by summer autumn. During drought, greatest negative deciduous forests croplands, woody savannas least impacted. This research provides scientific reference developing mitigation adaptation measures lessen disasters under changing climate.

Язык: Английский

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Comparison of bagging, boosting and stacking algorithms for surface soil moisture mapping using optical-thermal-microwave remote sensing synergies

CATENA, Год журнала: 2022, Номер 217, С. 106485 - 106485

Опубликована: Июнь 29, 2022

Язык: Английский

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Estimating the heavy metal contents in farmland soil from hyperspectral images based on Stacked AdaBoost ensemble learning

Ecological Indicators, Год журнала: 2022, Номер 143, С. 109330 - 109330

Опубликована: Авг. 23, 2022

Heavy metal pollution poses a huge challenge to the soil environment. With increasing level, traditional monitoring methods cannot quickly obtain information on large-area pollution. Therefore, large-scale mapping method with high precision is urgently needed effectively control heavy This study explored for concentrations through hyperspectral images. On this basis, new Stacked AdaBoost ensemble learning algorithm was constructed construct inversion model of contents. The characteristic spectral bands metals were extracted as input variables using Pearson's correlation coefficient and successive projections algorithm. three sets content data, prediction accuracy outcomes various machine compared. Furthermore, potential sources in area analyzed based Moran's index. results showed that relatively stable higher than models. For Cr, Cu, As, determination coefficients (R2) verification set 0.66, 0.61, 0.74, respectively. Afterward, used map concentration over area. suggested conditions soils Ganhetan caused by nature human activities. As agricultural most serious, an exceedance rate 38.66%. Industrial areas In summary, provides detailed reliable data ecological protection industrial control, allowing effective management sources.

Язык: Английский

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Prediction of soil organic carbon in black soil based on a synergistic scheme from hyperspectral data: Combining fractional-order derivatives and three-dimensional spectral indices

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 220, С. 108905 - 108905

Опубликована: Апрель 6, 2024

Язык: Английский

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Estimating soil salinity in mulched cotton fields using UAV-based hyperspectral remote sensing and a Seagull Optimization Algorithm-Enhanced Random Forest Model

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 221, С. 109017 - 109017

Опубликована: Май 7, 2024

Язык: Английский

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Hyperspectral inversion of heavy metal content in farmland soil under conservation tillage of black soils

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 2, 2025

Globally, heavy metal (HM) soil pollution is becoming an increasingly serious concern. Heavy metals in soils pose significant environmental and health risks due to their persistence, toxicity, potential for bioaccumulation. These often originate from anthropogenic activities such as industrial emissions, agricultural practices, improper waste disposal. Once introduced into the soil, they can bind particles, making them difficult remove, while potentially entering food chain through plant uptake or water contamination. Rapid access reliable data on HM viscosity necessary efficiently monitor remediated soils. Visible near-infrared reflectance spectroscopy (350–2500 nm) economical zero-pollution method that evaluate multiple concentrations simultaneously. Black a valuable resource helps guarantee security worldwide serve carbon reservoir, but its protection faces several challenges. Due long-term high-intensity development utilization severe over-exploitation of groundwater, arable land China's black area has been degraded. Using hyperspectral inversion content reduce destructive sample collection chemical better protect resources, steadily restore improve basic fertility land. Focusing region Jilin Province, this study explored correlation between three HMs, namely copper, zinc, cadmium, organic substances, clay minerals, ferromanganese oxides in-depth analysis samples using spectrometry. The spectra were transformed first-and second-order derivatives, scattering corrections, autoscales, Savitzky–Golay smoothing. successive projection algorithm was used screen characteristic bands (Table S1) establish link spectra. By employing support vector machine (SVM), random forest (RF), partial least squares (PLS) models, feature band-based modeling established. Moreover, optimal combinations spectral transforms models also examined. findings indicate RF model (R2 > 0.8, RPIQ 0) outperformed SVM PLS anticipating thus demonstrating superior accuracy. Understanding behavior developing effective management strategies are essential ensuring sustainable use protecting public health. This contributes large-scale monitoring systems assessments

Язык: Английский

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