Currently, there is an increasing interest in developing efficient and cost-effective treatment technologies to remediate per- and polyfluoroalkyl substances (PFAS) in water. Biochars (pristine and modified/engineered) can be a good candidate among porous pyrogenic carbonaceous materials for the sorptive removal of PFAS from water/wastewater. There is a need to focus on developing efficient, environmentally friendly, and cost-effective techniques for desorbing PFAS from spent biochars (pristine and modified/engineered) to enable potential reuse or suitable disposal of these adsorbents, facilitating their future full-scale application in the water sector. This review article briefly compiles the state-of-the-art knowledge on the: (i) application of pristine and modified/engineered biochars for the sorptive removal of PFAS from aqueous samples; (ii) regeneration/reuse techniques for the spent biochars; and (iii) economic analysis of their use in PFAS removal from water/wastewater. Further investigations on (i) better modifying/engineering biochars to remove specially short-chain PFAS species in real environmental water samples due to challenging nature of their removal using conventional treatment technologies; (ii) feasible low-energy, environmentally friendly, and cost-effective strategies for regeneration/reuse of the spent biochars (pristine and modified/engineered) and management of their end-of-life; and (iii) large-scale and continuous column sorption operation for the real water/wastewater samples are still desirable to apply biochars for PFAS removal at full-scale in the future.
Perfluorinated acids (PFAs) are a new class of persistent organic pollutants that are difficult to defluorinate or remove. The reductive degradation of various representative PFAs in a biomimetic system composed of vitamin B12 (VB12) as a catalyst and nano-zero-valent iron-nickel bimetal (nFe0/Ni0) as a reductant was investigated in this study. The effects of the self-structures of PFAs and the coexisting substances in natural water were also discussed. The results indicated that the defluorination and removal rates of PFAs were highly dependent on the length and terminal functional groups of the perfluorocarbon chain. Only Perfluorocarboxylates with C > 11 and Perfluorosulfonates with C > 6 were significantly degraded. Based on the analysis of the degradation products of perfluorobutanesulfonate (PFBS), perfluorohexanesulfonate (PFHxS), prefluorooctanesulfonate (PFOS), and 2-perfluoroctyl ethanol (8:2 FTOH), hydrolysis followed by the scission of C–S or C–C connecting the terminal functional groups was the dominant degradation pathway of long-chain PFAs instead of cleavage of C–C in the perfluorocarbon chain. The perfluorocarbon chain length affects the product type. It is speculated that the high bond dissociation energies of C–F bonds in short-chain PFAs hinder the occurrence of the decarboxylation-hydroxylation-elimination-hydrolysis (DHEH) pathway and make the addition of (–CF2–)n dominant. Meanwhile, the inhibition of SO42– removal by PFOS was significant, whereas humic acid, Cl–, and dissolved oxygen had only a slight influence. Overall, this study provides new insights on the degradation of PFAs containing multiple structures and highlights the impact of the self-structure on PFAs removal.
Polyethylene-based plastic mulch films are widely utilized in agriculture due to their benefits in improving soil conditions and crop yield. However, their degradation into microplastics has been shown to negatively impact plant growth and development, posing a significant source of plastic pollution in the agroecosystem. In response to this issue, the present study aimed to design an innovative bioremediation system based on PGPR (Pseudomonas aeruginosa), biochar, and UV treatment for the degradation of plastics. Additionally, the phytotoxic effects of plastic residues on the growth of Spinacia oleracea (spinach) were evaluated to understand the impact of plastic contamination on plant health. Bacterial strains were isolated from vegetable-cultivated soil with plastic mulch. The bacterial strain demonstrating the most effective plant growth-promoting properties and plastic degradation efficiency was identified as Pseudomonas aeruginosa (OP007126). Biochar was prepared from food waste and thoroughly characterized. Polyethylene (PE) was exposed to UV radiation to induce degradation. A glass house experiment was then designed to assess the effect of PGPR, biochar, and UV radiation on mitigating plastic-induced stress and promoting plant growth. Fourier transform infrared spectroscopy (FTIR) and weight loss measurement showed a maximum degradation of 62% with a combination of all treatments. PE negatively affected the morphology of the plant as it decreased the shoot and root fresh weight by up to 60%. Biochemical parameters of spinach were also affected by PE, as proline content increased by up to 45%. The use of amendments demonstrated effectiveness in alleviating the detrimental impact of PE on spinach plants, as evidenced by improvements in morphological, physiologic, and biochemical parameters. This approach presents a promising strategy to mitigate the detrimental effects of plastic mulch and warrants further investigation through field trials.
Microplastics have received increasing attention in soil ecosystems, and their potential impacts on soil properties have raised concerns. Pesticides are the most prevalent pollutants in soil, but their combined effects with microplastics on the soil environment have not been elucidated. In this study, polystyrene microplastics (PS MPs) and imidacloprid (IMI) were added to the soil to investigate their combined effects on soil physicochemical characteristics, nitrogen and phosphorus contents, related transformation activities, and the composition of nitrogen- and phosphorus-transforming microorganisms. The results revealed that the coexistence of PS MPs and IMI led to a significantly higher soil pH level and lower water-stable aggregate (WSA) content. Additionally, it increased the relative abundance of nitrogen- and phosphorus-transforming microorganisms, including ammonia-oxidizing archaea and bacteria, nitrite-oxidizing bacteria, heterotrophic denitrifying bacteria, phosphate-solubilizing bacteria. PS MPs increased the soil potential denitrification rate by 14.53% owing to a significantly higher pH level. However, this promotion disappeared when they combined with IMI. The coexistence of PS MPs and IMI caused a significant decrease in WSA content, thereby improving soil aeration and increasing the relative abundance of phosphate-solubilizing bacteria, which led to a 14.54% and 44.79% increase in soil phosphatase activity and Olsen-P content, respectively. Variance partitioning analysis revealed that the coexistence of PS MPs and IMI mainly influenced nitrogen and phosphorus transformations by altering soil pH and WSA content. These results reveal the combined effects of PS MPs and IMI on soil nitrogen and phosphorus transformations and elucidate soil environmental risks associated with microplastics and pesticides.
Phytoplankton serve as vital indicators of eutrophication levels. However, relying solely on phytoplankton parameters, such as chlorophyll-a, limits our comprehensive understanding of the intricate eutrophication conditions in natural lakes, particularly in terms of timely analysis of changes in limiting nutrients and their concentrations. This study presents machine learning (ML) models for predicting and identifying lake eutrophication. Five tree-based ML models were developed using the latest data on hydrological, water quality, and meteorological parameters obtained from 34 sites in the Huating Lake basin over 5 months. The extreme gradient boosting model exhibited high accuracy in predicting the total nitrogen/total phosphorus ratio (TN/TP) (R2 = 0.88; RMSE = 24.60; MAPE = 26.14%). Analysis of the TN/TP ratio and output eigenvalue weight revealed that phosphorus plays a crucial role in eutrophication, probably because of the low-flow and deep-water characteristics of the basin. Furthermore, the light gradient boosting machine model exhibited outstanding performance and high accuracy in predicting phytoplankton parameters, especially the Shannon index (H′) (R2 = 0.92; RMSE = 0.11; MAPE = 4.95%). The mesotrophic classification of the Huating Lake determined using the H′ threshold, coincided with the findings from the H′ analysis. Future research should cover a wider range of pollution sources and spatiotemporal dimensions to further validate our findings. Overall, this study highlights the potential of incorporating the TN/TP ratio and phytoplankton parameters into ML techniques for effective monitoring and management of environmental conditions.
