Air Pollutants Removal Using Biofiltration Technique: A Challenge at the Frontiers of Sustainable Environment

IF 4.3 Q2 ENGINEERING, CHEMICAL
Karamveer Sheoran, Samarjeet Singh Siwal*, Deepanshi Kapoor, Nirankar Singh, Adesh K. Saini, Walaa Fahad Alsanie and Vijay Kumar Thakur*, 
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引用次数: 14

Abstract

Air pollution is a central problem faced by industries during the production process. The control of this pollution is essential for the environment and living organisms as it creates harmful effects. Biofiltration is a current pollution management strategy that concerns removing odor, volatile organic compounds (VOCs), and other pollutants from the air. Recently, this approach has earned vogue globally due to its low-cost and straightforward technique, effortless function, high reduction efficacy, less energy necessity, and residual consequences not needing additional remedy. There is a critical requirement to consider sustainable machinery to decrease the pollutants arising within air and water sources. For managing these different kinds of pollutant reductions, biofiltration techniques have been utilized. The contaminants are adsorbed upon the medium exterior and are metabolized to benign outcomes through immobilized microbes. Biofiltration-based designs have appeared advantageous in terminating dangerous pollutants from wastewater or contaminated air in recent years. Biofiltration uses the possibilities of microbial approaches (bacteria and fungi) to lessen the broad range of compounds and VOCs. In this review, we have discussed a general introduction based on biofiltration and the classification of air pollutants based on different sources. The history of biofiltration and other mechanisms used in biofiltration techniques have been discussed. Further, the crucial factors of biofilters that affect the performance of biofiltration techniques have been discussed in detail. Finally, we concluded the topic with current challenges and future prospects.

Abstract Image

利用生物过滤技术去除空气污染物:可持续环境前沿的挑战
空气污染是工业生产过程中面临的一个核心问题。控制这种污染对环境和生物至关重要,因为它会产生有害影响。生物过滤是一种当前的污染管理策略,涉及去除空气中的气味、挥发性有机化合物(VOCs)和其他污染物。近年来,该方法因其成本低,技术简单,功能轻松,还原效果高,能源消耗少,不需要额外补救的残余后果而在全球范围内流行。有一个关键的要求是考虑可持续的机制,以减少空气和水源中产生的污染物。为了管理这些不同种类的污染物减少,生物过滤技术已经被使用。污染物被吸附在介质外部,并通过固定化微生物代谢为良性结果。近年来,基于生物过滤的设计在消除废水或污染空气中的危险污染物方面表现出优势。生物过滤利用微生物方法(细菌和真菌)的可能性来减少各种化合物和挥发性有机化合物。本文主要介绍了生物过滤技术的概况,并对不同来源的空气污染物进行了分类。本文讨论了生物过滤技术的发展历史和生物过滤技术中使用的其他机制。此外,还详细讨论了影响生物过滤技术性能的生物过滤器的关键因素。最后,我们对课题进行了总结,提出了当前面临的挑战和未来的展望。
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来源期刊
ACS Engineering Au
ACS Engineering Au 化学工程技术-
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期刊介绍: )ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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