Field Environment Research Articles

Impacts on Health, Environment and Quality of Life in the Post-Covid-19 Pandemic Period

Objective: To investigate how the pandemic and the post-COVID-19 scenario may impact current and future plans in health (medical area), the environment, and the population's quality of life. Theoretical Framework: In 2019, the world began to live as a hostage to an infectious disease caused by the SARS-CoV-2 coronavirus. As uncertainty reigns, the severity of the situation has shown that it could have social, health, educational, economic, and environmental aspects. Method: The methodology adopted for this research comprises a bibliographic review based on books, cataloged scientific articles being published on digital platforms including Scientific Library Online (SciELO), Pubmed, Periódico Capes, Cochrane, and Google Scholar, using the descriptors: COVID-19; quality of life; environment; health; and their respective synonyms, in Portuguese and English, published between 2015 and 2024. The exclusion criteria used in this study were duplicate articles in more than one database, with similar titles and that did not cover the topic, as well as articles published before 2015 in Portuguese and English. The main aspects analyzed for inclusion were the year of publication, type of study, language, objectives and main findings, according to the relevance of the original and current topic. Therefore, considering the inclusion and exclusion criteria, we made a cut of works published in the last 9 years and in the end 31 works were selected for the construction of this study. Results and Discussion: The results obtained revealed that all social spheres were, and may still be, affected unequally by the pandemic, since it is a situation of unknown nature, which is intensified every day by globalization and social inequalities. Direct impacts on the economy and jobs, as well as indirect effects of learning losses among children who are out of school. In terms of health and the impact on quality of life, we found changes in mental health, with an increase in the diagnosis of depression among adults. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the fields of health, environment and education. These implications can cover areas of health promotion, economics and public and private management. Originality/Value: This study contributes to the literature by addressing a current topic with extreme social relevance that prioritizes deepening knowledge in the area that has changed humanity the most in current times: the COVID-19 Pandemic. Furthermore, it analyzes the real impacts of this historical and unique moment in the global context, with a greater focus on health, the environment and the quality of life of the human population.

Genetic and Environmental Patterns Underlying Phenotypic Plasticity in Flowering Time and Plant Height in Sorghum.

Phenotypic plasticity is the property of a genotype to produce different phenotypes under different environmental conditions. Understanding genetic and environmental factors behind phenotypic plasticity helps answer some longstanding biology questions and improve phenotype prediction. In this study, we investigated the phenotypic plasticity of flowering time and plant height with a set of diverse sorghum lines evaluated across 14 natural field environments. An environmental index was identified to quantitatively connect the environments. Reaction norms were then obtained with the identified indices for genetic dissection of phenotypic plasticity and performance prediction. Genome-wide association studies (GWAS) detected different sets of loci for reaction-norm parameters (intercept and slope), including 10 new genomic regions in addition to known maturity (Ma1) and dwarfing genes (Dw1, Dw2, Dw3, Dw4 and qHT7.1). Cross-validations under multiple scenarios showed promising results in predicting diverse germplasm in dynamic environments. Additional experiments conducted at four new environments, including one from a site outside of the geographical region of the initial environments, further validated the predictions. Our findings indicate that identifying the environmental index enriches our understanding of gene-environmental interplay underlying phenotypic plasticity, and that genomic prediction with the environmental dimension facilitates prediction-guided breeding for future environments.

Estimate of in-band eddy current effect in space gravitational wave detection

Abstract In space detection of gravitational waves (GWs), the presence of a low-frequency varying magnetic field will generate eddy currents in the test mass, resulting in a varying magnetic moment. This magnetic moment will couple with a constant magnetic field gradient, producing residual acceleration within the frequency band of GW detection, causing the test mass to deviate from the free-falling mode. However, this effect has not yet been studied clearly in the noise budget for TianQin and LISA Pathfinder since the constant DC magnetic susceptibility was applied to quantify the varying magnetic moment. This paper utilizes the parameter of alternating current (AC) magnetic susceptibility to define this process, and further analyzes and evaluates the effect. In a general magnetic field environment, the contribution of this effect to TianQin acceleration noise reaches 20\% from 0.1 mHz to 3 mHz. The contribution to LISA noise is less than 10\% from $10^{-4}$ to 0.1 Hz, and less than 10\% below $10^{-4}$ Hz. This effect does not have a potential limit on LISA low-frequency science down to 20 $\mu$Hz [Phys. Rev. Lett. 120, 061101 (2018)].

Implementasi Program Peningkatan Edukasi di bidang Lingkungan Hidup

The implementation of the Education Improvement Program in the field of Environment is a strategic effort to increase public awareness and knowledge about environmental issues. The program is designed to meet increasingly complex environmental challenges by providing an effective and sustainable education. This study evaluates the effectiveness of various environmental education methods, including seminars, workshops, and media campaigns. Through a data-based approach, the analysis was carried out to measure the impact of the program on changes in participants' attitudes and behaviors towards environmental issues. The results show that interactive and participatory methods are more successful in increasing community understanding and engagement. This finding is expected to be a reference for the development of better environmental education programs in the future.

A generalized model for accurate wheat spike detection and counting in complex scenarios

Wheat is a crucial crop worldwide, and accurate detection and counting of wheat spikes are vital for yield estimation and breeding. However, these tasks are daunting in complex field environments. To tackle this, we introduce RIA-SpikeNet, a model designed to detect and count wheat spikes in such conditions. First, we introduce an Implicit Decoupling Detection Head to incorporate more implicit knowledge, enabling the model to better distinguish visually similar wheat spikes. Second, Asymmetric Loss is employed as the confidence loss function, enhancing the learning weights of positive and hard samples, thus improving performance in complex scenes. Lastly, the backbone network is modified through reparameterization and the use of larger convolutional kernels, expanding the effective receptive field and improving shape information extraction. These enhancements significantly improve the model’s ability to detect and count wheat spikes accurately. RIA-SpikeNet outperforms the state-of-the-art YOLOv8 detection model, achieving a competitive 81.54% mAP and 90.29% R2. The model demonstrates superior performance in challenging scenarios, providing an effective tool for wheat spike yield estimation in field environments and valuable support for wheat production and breeding efforts.

Beliefs in Online Professional Learning in Early Mathematics Teaching and Their Effects on Course Engagement

This study focused on the effects of an early math online professional learning course offered to preschool teachers. The course was designed to inform participants' knowledge of developmental progressions and promote daily mathematics instruction that encouraged students to view their world through a mathematical lens. A survey of preschool teachers' beliefs was administered to participants of the course to determine if participants' beliefs changed significantly and how their pre-course beliefs influenced their engagement in the course. Findings indicate that the course impacted preschool teachers regardless of their area of responsibility, education level, or experience level. The teachers' comfort with teaching math to young children and perspectives about age appropriateness of mathematics were both positively influenced by the course. The teachers with the most positive initial beliefs had a higher rate of course completion. Implications for the field of preschool teacher education and online professional learning environments are discussed.

Preface: 3rd International Conference on Portfolios, Global Marketing and Economic Environment (PGMEE 2024)

2024 3rd International Conference on Portfolios, Global Marketing and Economic Environment (PGMEE 2024) was held in Sao Paulo, Brazil during September 07-08, 2024. This conference aims to provide an academic sharing and exchanging platform for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of portfolios, financial security, risk management, global marketing, asset pricing, investment policy and economic environment. The success of PGMEE 2024 is due to the high scientific level of all the contributions as well as to the enthusiasm of all the attendees. The member of the technical committee did a precious job in selecting the papers that were accepted for presentation and for inclusion in this book of proceedings among those that were initially submitted. Beside the authors, participants, we would like to thank the members of the organizing committee, reviewers and volunteers, whose work was fundamental for assuring the smooth running of the conference. We hope PGMEE 2024 can develop into persistent success in future years, involving participants and speakers from all corners of the world. And we believe that with the strong support of all participants, professors, scholars, this conference will be more distinctive. PGMEE Organizing Committees Sao Paulo, Brazil

Microwave Ignition of Thermites

AbstractThis study investigates the microwave ignition behavior of a range of thermites of aluminum, boron, titanium, and tantalum fuels with oxides of Bi2O3, CuO, and Fe2O3. In order to gain insight into the modes of energy transfer leading to ignition, thermites are heated in either a purely electric or magnetic field environment within a single‐mode 2.45 GHz resonant cavity with electric field strengths of 40 to 110 kV/m and magnetic field strengths of 22 to 258 A/m. Thermite stoichiometry is varied as well as particle size and thermite mass. The shortest ignition delays in electric and magnetic fields were found to be 1.37 s (nAl and CuO) and 0.87 s (nAl and CuO), respectively. The use of a variety of carbon susceptors to shorten ignition delay is also studied. Carbon susceptors are found to appreciably shorten ignition delays to as short as 140 and 170 ms for the E and B field respectively (nAl and CuO with multiwalled carbon nanotubes). The results of this work are informative on thermite component choice and the preferred mechanism (electric vs magnetic field) of heating for various thermite compositions for consideration of the increasingly popular ignition via electromagnetic fields.

THE BRAZILIAN LEGAL SYSTEM AND THE INTERNATIONAL ENVIRONMENTAL PRINCIPLES

This article aims to analyze the environmental principles established in the international order and recognized by the Brazilian legal system, in particular the 1988 constitutional text, with the aim of evaluating the effects of international legislation with regard to environmental matters, based on verification of a staggered and more accentuated regulatory development in the environmental field. The aim was to define the parameters of the new world economic order and the importance attributed to the outstanding principles of precaution, sustainable development and prevention, with a view to consolidating a relevant tool for promoting environmental protection. In this sense, by synthesizing a study on the adoption and adequacy of the principle elements of the international environmental order, an investigative aspect is created to promote awareness of the primacy of an environment that receives collective care both at a global and national level. The strengthening of international environmental law was also a concern of this article, even though it was a brief analysis, so that it shows the exact notion that the issue must involve all social actors, from individuals and even the most complex state structure, with the goal of defining and applying a normative framework on environmental issues, in the international sphere and its applicability in national territory, through the due process of internalization of treaties and, in particular, the economic order in the 1988 Constitution, facing the challenges arising from growth world population and the urgent need to confront the catastrophic effects of the process of industrialization and large-scale consumption, considering environmental sustainability.

Interactive strategy of shared control vehicle and automated vehicles based on adaptive non-cooperative game

Considering the complex traffic environment in the future, an interactive strategy between human-machine shared control vehicle (HSCV) and automated vehicles (AVs) based on the adaptive non-cooperative game (NCG) theory is proposed to ensure the safety of vehicles interaction control involving drivers with different characteristics. In HSCV, first, considering the environmental risk potential field (ERPF) and the human-machine conflict coefficient, an adaptive weight distribution method is designed to realize the weight distribution between a driver and an automation system. Subsequently, the steering angle command imposed by a driver is introduced into the game solving process between HSCV and AVs, enabling adaptive dynamic game through weight adjustment. During V2V interaction, based on NCG and distributed model predictive control, a motion planning controller (MOPC) is designed to integrate the optimal solution problem of path planning and tracking control and solve the interaction problem with constraints. Two typical interactive scenarios are used to verify the feasibility of the strategy. The results demonstrate that the interaction strategy considering the different drivers’ operating commands not only realizes the interaction between a driver and an ego vehicle but also realizes the interaction between an ego vehicle and nearby vehicles to ensure the safety of vehicles.

Automated lepidopteran pest developmental stages classification via transfer learning framework.

The maize crop is highly susceptible to damage caused by its primary pests, which poses considerable challenges in manually identifying and controlling them at various larval developmental stages. To mitigate this issue, we propose an automated classification system aimed at identifying the different larval developmental stages of 23 instars of 4 major lepidopteran pests: the Asian corn borer, Ostrinia furnacalis (Guenée; Lepidoptera: Crambidae), the fall armyworm, Spodoptera frugiperda (J.E. Smith; Lepidoptera: Noctuidae), the oriental armyworm, Mythimna separata (Walker; Lepidoptera: Noctuidae), and the tobacco cutworm, Spodoptera litura (Fabricius; Lepidoptera: Noctuidae). Employing 5 distinct Convolutional Neural Network architectures-Convnext, Densenet121, Efficientnetv2, Mobilenet, and Resnet-we aimed to automate the process of identifying these larval developmental stages. Each model underwent fine-tuning using 2 different optimizers: stochastic gradient descent with momentum and adaptive moment estimation (Adam). Among the array of models tested, Densenet121, coupled with the Adam optimizer, exhibited the highest classification accuracy, achieving an impressive 96.65%. The configuration performed well in identifying the larval development stages of all 4 pests, with precision, recall, and F1 score evaluation indicators reaching 98.71%, 98.66%, and 98.66%, respectively. Notably, the model was ultimately tested in a natural field environment, demonstrating that Adam_Densenet121 model achieved an accuracy of 90% in identifying the 23 instars of the 4 pests. The application of transfer learning methodology showcased its effectiveness in automating the identification of larval developmental stages, underscoring promising implications for precision-integrated pest management strategies in agriculture.

Lightweight Detection of Broccoli Heads in Complex Field Environments Based on LBDC-YOLO

Robotically selective broccoli harvesting requires precise lightweight detection models to efficiently detect broccoli heads. Therefore, this study introduces a lightweight and high-precision detection model named LBDC-YOLO (Lightweight Broccoli Detection in Complex Environment—You Look Only Once), based on the improved YOLOv8 (You Look Only Once, Version 8). The model incorporates the Slim-neck design paradigm based on GSConv to reduce computational complexity. Furthermore, Triplet Attention is integrated into the backbone network to capture cross-dimensional interactions between spatial and channel dimensions, enhancing the model’s feature extraction capability under multiple interfering factors. The original neck network structure is replaced with a BiFPN (Bidirectional Feature Pyramid Network), optimizing the cross-layer connection structure, and employing weighted fusion methods for better integration of multi-scale features. The model undergoes training and testing on a dataset constructed in real field conditions, featuring broccoli images under various influencing factors. Experimental results demonstrate that LBDC-YOLO achieves an average detection accuracy of 94.44% for broccoli. Compared to the original YOLOv8n, LBDC-YOLO achieves a 32.1% reduction in computational complexity, a 47.8% decrease in parameters, a 44.4% reduction in model size, and a 0.47 percentage point accuracy improvement. When compared to models such as YOLOv5n, YOLOv5s, and YOLOv7-tiny, LBDC-YOLO exhibits higher detection accuracy and lower computational complexity, presenting clear advantages for broccoli detection tasks in complex field environments. The results of this study provide an accurate and lightweight method for the detection of broccoli heads in complex field environments. This work aims to inspire further research in precision agriculture and to advance knowledge in model-assisted agricultural practices.

Electrocombustion Characteristics of Iron Particle-Laden Methanol and Ethanol Droplets in a Direct Current Field

ABSTRACT This study investigates the electrocombustion and atomization behavior of single droplets (2.5 wt.% Fe) of ethanol (EtOH) and methanol (MeOH) fuels at the droplet scale. The experiments utilize a system with two opposing plate electrodes of varying distances (200, 150, and 100 mm) and both negative (↓) and positive (↑) polarizations within a vertical direct current (DC) electric field. The results show that for EtOH and EtOH/Fe droplets, the flame envelope changes to a spherical form at (↓) and (↑) polarizations at 100 mm plate spacing, while for MeOH and MeOH/Fe droplets, the flame envelope changes to a spherical form at (↓) and (↑) polarizations at 200, 150 and 100 mm plate spacing. Increasing electric field strength reduced the micro-explosion tendency of Fe particles in the flame region and the micro-explosion intensity of Fe particles was found to be higher in ethanol droplets than in methanol. No systematic relationship could be established between the electric field effect and the presence of Fe particles. The MeOH/Fe/150(↑) droplet exhibited the lowest extinction time of 1050 ms. The electric field fundamentally alters the secondary atomization process of the fuel droplets. Notably, the diameter regression of all MeOH-based fuel droplets deviates significantly from a linear relationship. The investigation into the combustion behavior of pure EtOH, MeOH, and their Fe-blended counterparts within an electric field environment suggests that MeOH and MeOH/Fe fuels exhibit superior combustion characteristics. However, further research is necessary to fully elucidate these findings.

A Review: Recent Advances of Piezoelectric Photocatalysis in the Environmental Fields.

Piezoelectric photocatalysis can effectively suppress the recombination of electron holes during the course of photocatalysis, which has been widely applied in environmental and energy catalysis. Its advantage is that when the piezoelectric effect happens, a built-in electric field is formed inside the catalyst, which improves the separation efficiency of photogenerated charge carriers and obtains more excellent photocatalytic performance. The efficient conversion of mechanical energy to chemical energy can be realized through the synergistic effect of the piezoelectric effect, and photocatalysis is greatly significant in solving the energy crisis and providing environmental protection. Therefore, we organized a more complete review to better understand the mechanism and system of piezoelectric photocatalysis. We briefly introduce the principle of the piezoelectric effect, the existing types of piezoelectric photocatalysts, the practical application scenarios, and the future challenges and feasible methods to improve catalytic efficiency. The purpose of this review is to help us broaden the idea of designing piezoelectric photocatalysts, clarify the future research direction, and put it into more fields of environmental protection and energy reuse.

Antibacterial and antifungal activities of Platycladus orientalis leaf extract-mediated Fe2O3 and Ce-doped Fe2O3 nanoparticles

Green synthesis of nanomaterials harnesses naturally occurring materials, including plant extracts, to offer environmentally friendly alternatives to conventional biomedicine, agriculture, and other field applications. This study explores the green route to Fe2O3 and cerium-doped Fe2O3 (Ce-doped Fe2O3) nanoparticles synthesized for the first time using the leaf extract of Platycladus orientalis. The synthesized nanoparticles were characterized for their structural, morphological, chemical, and optical properties. The hematite phase of Fe2O3 nanoparticles with spherical morphology was obtained. The introduction of Ce as a dopant into Fe2O3 increased the lattice strain of Ce-doped Fe2O3 nanoparticles (0.51%) compared to pristine Fe2O3 (0.46%) even though the size of both nanomaterials was similar. Compared to pristine Fe2O3 nanoparticles, Ce-doped Fe2O3 nanoparticles also demonstrated enhanced antimicrobial and antifungal activities against Escherichia coli, Enterococcus faecalis, Listeria monocytogenes, Penicillium chrysogenum, Aspergillus niger, and Mucor mucedo. The green-synthesized Ce-doped Fe2O3 nanoparticles possess potential for application in biomedical and environmental fields based on their relevance to human health and food safety, diversity in microbial characteristics, and potential for resistance to conventional treatments.

Strain analysis and preliminary test of an all-superconducting high-field magnet generating 32.4 T direct-current magnetic field

Abstract A higher available magnetic field can give more flexibility for significant research and constructions. Inserting feasible high-temperature-superconducting (HTS) magnet inside low-temperature-superconducting (LTS) external is becoming an efficient method to build ultra-high-field (UHF) magnets. However, HTS insert magnets exhibited concentration of magnetic strain during the energization, significantly owing to the screening-current effect. This phenomenon affect the structural integrity of HTS magnets, posing a difficulty for UHF magnets to reach a center field larger than 30 T. In this paper, we report the recent progress of the 35 T all-superconducting UHF magnet project. The full-cycle development of this homemade UHF magnet was a strong collaboration with multiple domestic institutions in China. We used commercial REBa2Cu3O7-x (RE = rare earth element, REBCO) conductors to wind the 20 T HTS insert. Specifically, we optimized the electromagnetic design of this HTS insert with consideration of screening-current induced strain. We applied the no-insulation and metal-as-insulation winding techniques simultaneously to balance the time constant of the two nested REBCO coils. During the excitation test, the HTS insert maintained a 256 A operation current as designed for nearly 18 hours. With the energization of LTS external magnet, the entire facility reached a center field larger than 20 T for 16 hours, 30 T for 6.35 hours and 32 T for 2 hours. It finally reached a 32.4 T center field, at which point the LTS external quenched, inducing the HTS insert to quench as well. After quench, the HTS magnet can maintained 229 A operation current during the postmortem standalone test. This 32.4 T result exhibits effectiveness of considering the screening-current induced strain to enhance the structural integrity of REBCO magnets, and verifies the high reliability of REBCO magnets by generating a long-duration high field environment without any quench accident originating from the REBCO magnet.

A multi-source domain feature adaptation network for potato disease recognition in field environment.

Accurate identification of potato diseases is crucial for reducing yield losses. To address the issue of low recognition accuracy caused by the mismatch between target domain and source domain due to insufficient samples, the effectiveness of Multi-Source Unsupervised Domain Adaptation (MUDA) method in disease identification is explored. A Multi-Source Domain Feature Adaptation Network (MDFAN) is proposed, employing a two-stage alignment strategy. This method first aligns the distribution of each source-target domain pair within multiple specific feature spaces. In this process, multi-representation extraction and subdomain alignment techniques are utilized to further improve alignment performance. Secondly, classifier outputs are aligned by leveraging decision boundaries within specific domains. Taking into account variations in lighting during image acquisition, a dataset comprising field potato disease images with five distinct disease types is created, followed by comprehensive transfer experiments. In the corresponding transfer tasks, MDFAN achieves an average classification accuracy of 92.11% with two source domains and 93.02% with three source domains, outperforming all other methods. These results not only demonstrate the effectiveness of MUDA but also highlight the robustness of MDFAN to changes in lighting conditions.

A Review on Bioflocculant-Synthesized Copper Nanoparticles: Characterization and Application in Wastewater Treatment.

Copper nanoparticles (CuNPs) are tiny materials with special features such as high electric conductivity, catalytic activity, antimicrobial activity, and optical activity. Published reports demonstrate their utilization in various fields, including biomedical, agricultural, environmental, wastewater treatment, and sensor fields. CuNPs can be produced utilizing traditional procedures; nevertheless, such procedures have restrictions like excessive consumption of energy, low production yields, and the utilization of detrimental substances. Thus, the adoption of environmentally approachable "green" approaches for copper nanoparticle synthesis is gaining popularity. These approaches involve employing plants, bacteria, and fungi. Nonetheless, there is a scarcity of data regarding the application of microbial bioflocculants in the synthesis of copper NPs. Therefore, this review emphasizes copper NP production using microbial flocculants, which offer economic benefits and are sustainable and harmless. The review also provides a characterization of the synthesized copper nanoparticles, employing numerous analytical tools to determine their compositional, morphological, and topographical features. It focuses on scientific advances from January 2015 to December 2023 and emphasizes the use of synthesized copper NPs in wastewater treatment.

Continuous recovery of tellurium and cadmium from simulated CdTe leachates using a fixed-bed-column adsorption system

Rare element resource (Te) loss and heavy metal (Cd) pollution, derived from waste photovoltaic CdTe cells, have attracted considerable attention in the cleaner production and environmental protection field. However, there are several technical barriers in conventional adsorption strategies for the continuous recovery Te(Ⅳ) and Cd(Ⅱ) due to single-component recovery, inefficient adsorbent utilization and less automation. Herein, this work presented a fixed-bed-column adsorption system for the continuous adsorption recovery of tellurium and cadmium from a simulated CdTe leachate using functional sludge-based adsorption fillers (LDO/SF and EDTA@LDH/SF) that prepared from water-processing sludge via hydrothermal synthesis, thermal activation and surface modification technologies. Breakthrough curves were analyzed for adsorption columns, considering initial concentration, flow rate, and filler height, with parameters evaluated using the Thomas and BDST models to determine the optimal separation parameters. During the continuous adsorption process, the column adsorption system with the filler layer height of 4 cm and liquid delivery rate of 1 mL/min can be used for continuous separation of more than 1000 mL of a simulated CdTe leachate and exhibits adsorption efficiencies of more than 96% and 82% for Te(Ⅳ) and Cd(Ⅱ), respectively. More importantly, the elution procedure was used to treat the column adsorption system with ion adsorption acceptances of 83% and 90% for Te(Ⅳ) and Cd(Ⅱ), respectively. Meanwhile, the functional sludge-based fillers demonstrated great regeneration and recycling capabilities, thus maximizing the utilization of adsorbents and saving treatment costs. This study has established a robust technical solution for the continuous recovery of tellurium and cadmium from simulated leachates, providing a practical framework for evaluating the efficiency of adsorption filler columns in actual applications.

Biosurfactants: Chemical Properties, Ecofriendly Environmental Applications, and Uses in the Industrial Energy Sector

The exploitation of nature and the increase in manufacturing production are the cause of major environmental concerns, and considerable efforts are needed to resolve such issues. Oil and petroleum derivatives constitute the primary energy sources used in industries. However, the transportation and use of these products have huge environmental impacts. A significant issue with oil-related pollution is that hydrocarbons are highly toxic and have low biodegradability, posing a risk to ecosystems and biodiversity. Thus, there has been growing interest in the use of renewable compounds from natural sources. Biosurfactants are amphipathic microbial biomolecules emerging as sustainable alternatives with beneficial characteristics, including biodegradability and low toxicity. Biosurfactants and biosurfactant-producing microorganisms serve as an ecologically correct bioremediation strategy for ecosystems polluted by hydrocarbons. Moreover, synthetic surfactants can constitute additional recalcitrant contaminants introduced into the environment, leading to undesirable outcomes. The replacement of synthetic surfactants with biosurfactants can help solve such problems. Thus, there has been growing interest in the use of biosurfactants in a broad gamut of industrial sectors. The purpose of this review was to furnish a comprehensive view of biosurfactants, classifications, properties, and applications in the environmental and energy fields. In particular, practical applications of biosurfactants in environmental remediation are discussed, with special focus on bioremediation, removal of heavy metals, phytoremediation, microbial enhanced oil recovery, metal corrosion inhibition, and improvements in agriculture. The review also describes innovating decontamination methods, including nanobioremediation, use of genetically modified microorganisms, enzymatic bioremediation, modeling and prototyping, biotechnology, and process engineering. Research patents and market prospects are also discussed to illustrate trends in environmental and industrial applications of biosurfactants.