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Concern over microplastics (MPs) in the environment is rising. Microplastics are generally known to exist in aquatic settings, but less is known about their occurrence in soil ecosystems. When plastic waste builds up in agricultural areas, it can have a negative impact on the environment and food sources, as well as have an indirect effect on all trophic levels of the food chain. This paper addresses the relationship between microplastics and the management of plastic waste, which contributes to their accumulation, and it describes the sources and the movement processes of microplastics in agricultural soils as a result of natural events and disasters. Evaluating the impact of weather on coastal microplastic contamination is critical, as extreme weather events have become more frequent in recent years. This study sheds light on how weather patterns affect the dispersion of plastic waste in terrestrial habitats, including the impacts of seasonality and extreme weather. According to the results of this review, typhoons, monsoons, rainfall, and floods contribute significantly more microplastics to the surface sediment through surface runoff and wind transport, particle redistribution caused by agitated waves, and fragmentation under intense abrasion forces. Severe weather conditions have the potential to disperse larger and more varied kinds of microplastics. [ABSTRACT FROM AUTHOR]

Concern over microplastics (MPs) in the environment is rising. Microplastics are generally known to exist in aquatic settings, but less is known about their occurrence in soil ecosystems. When plastic waste builds up in agricultural areas, it can have a negative impact on the environment and food sources, as well as have an indirect effect on all trophic levels of the food chain. This paper addresses the relationship between microplastics and the management of plastic waste, which contributes to their accumulation, and it describes the sources and the movement processes of microplastics in agricultural soils as a result of natural events and disasters. Evaluating the impact of weather on coastal microplastic contamination is critical, as extreme weather events have become more frequent in recent years. This study sheds light on how weather patterns affect the dispersion of plastic waste in terrestrial habitats, including the impacts of seasonality and extreme weather. According to the results of this review, typhoons, monsoons, rainfall, and floods contribute significantly more microplastics to the surface sediment through surface runoff and wind transport, particle redistribution caused by agitated waves, and fragmentation under intense abrasion forces. Severe weather conditions have the potential to disperse larger and more varied kinds of microplastics.

This study contributes to the current state of knowledge by highlighting the physical–chemical interactions between biochar and dyes. The removal of Acid Orange 7 (AO7) dye by a modified biochar obtained from the wastes of mandarin peels (MPs) has been investigated in this work. A dehydration procedure with 80% H2SO4 under reflux was applied to produce an innovative biochar from MPs and then boiled with H2O2 and followed by boiling with triethylenetetramine to make mandarin biochar-C-TETA (MBCT). FTIR, SEM, EDX, BJH, BET, TGA, and DTA analyses were applied to investigate the MBCT. FTIR analysis showed an additional peak that confirmed the addition of the NH2 group to the MBCT structure. An amorphous carbon structure was also confirmed by XRD analysis. The AO7 dye solution pH was proved to give the best absorption at pH 2.0. Significant removal of AO7 dye 99.07% using an initial concentration of 100 mg/L of AO7 dye and a 0.75 g/L MBCT. The Langmuir (LNR) and Freundlich (FRH) isotherm models investigated the experimental results. The LNR was best suited to handle the working MBCT data. The maximum adsorption capacity (Qm) calculated for the MBCT was 312.5 mg/g using 0.25 g/L of the MBCT. Kinetic studies were conducted using the intraparticle diffusion (IND), film diffusion (FD), pseudo-first-order (PFOR), and pseudo-second-order (PSOR) models. The absorption rate was calculated using the ultimate value of the linear regression coefficient (R2 > 0.99), and the PSOR rate model was found to ideally describe the absorption process. The point of zero charge (pHPZC) was found to be 10.17. The electrostatic attractive-forces between the sorbent surface positively charged sites and negatively charged anionic dye molecules were the primary mechanism of the MBCT sorption of the AO7 dye's anion absorption. The results indicate that the manufactured MBCT adsorbent may be useful for removing the AO7 dye from wastewater. MBCT can be used repeatedly for up to six cycles without dropping its absorption efficiency. [ABSTRACT FROM AUTHOR]

Context. The usual strategy for monitoring of eutrophication process is the use of traditional limnological methods, based on laboratory analysis. These procedures involve costly and time consuming analyses, usually with in vitro methodologies, which can still have limitations in terms of sensitivity and reliability, if poorly managed. Phytoplankton pigments, such as chlorophyll-a (Chl-a), are highly fluorescent and can provide the environmental status of water bodies. Aims. This study aims to analyse, compare and evaluate an estimation of Chl-a through fluorescence in public water sources in the Brazilian cerrado. Exploratory statistical analyses were conducted by using absolute fluorescence units (AFU) and relative fluorescence units (RFU) compared with traditional laboratory data (standard procedure for the determination of Chl-a by spectroscopic methods) to evaluate the significance of differences in estimating Chl-a concentration. Subsequently, empirical models, based on spectral band combinations, were generated to convert fluorescence measurement in Chl-a concentration, by linear regression. Key results. The generated model found a strong correlation and coefficient of determination (r = 0.88; R² = 0.78). The efficiency of the model was also confirmed by statistical indicators (RMSE = 1.27, MAPE = 26.72 and BIAS = -6.32). Conclusions. We concluded that the estimate of Chl-a through RFU was better than through AFU. Implications. Therefore, based on the results of this study, it is recommended that RFU be used to obtain more precise and accurate estimates of Chl-a concentration through empirical models based on linear regression. [ABSTRACT FROM AUTHOR]