Environmental Pollution Monitoring Research Articles

EVALUASI SISTEM DAN DAMPAK LINGKUNGAN PENGELOLAAN AIR TERPRODUKSI PADA SUMUR X1 PT MGBI LAPANGAN WUNUT

PT Minarak Gas Brantas Inc.'s operations in the Wunut Field involve the production of waste in various forms, primarily liquid waste, with produced water being the most significant type. Proper management of this produced water waste is crucial to prevent environmental pollution and ensure economic and environmental sustainability. The company manages this waste by reinjecting it into the reservoir to prevent groundwater contamination. To ensure the effectiveness of this reinjection process, they have created a groundwater flow pattern map (flow net) at three locations near the injection well: LP1 in Keduung Boto Village, LP2 in Candi Pari Village, and LP3 in Candi Pari Village, all in Sidoarjo Regency. This helps in understanding the potential spread of pollutants in the soil and underground water, aiding in environmental pollution monitoring and managment.The groundwater from this area is used for various human activities like bathing, cooking, and washing. However, based on water quality standards outlined in Ministry of Health Regulation No. 2 of 2023, the produced water from Well X-1 in the Wunut Field does not meet the required TDS (Total Dissolved Solids) content standards due to a decline in hydrocarbon fluid production, resulting in a separator efficiency of 74,86%. Additionally, lab tests and flow net results indicate that the TDS levels in LP1, LP2, and LP3 do not meet the sanitation and hygiene water quality standards, suggesting potential seepage in these locations that could contaminate groundwater. Keywords: Oil; Gas Produced Water; Gas Separator Eficiency; Groundwater Flow

Estimating nitroxynil residues in food samples and surface water using two different sustainable chemical sensing techniques: Comparative greenness, whiteness, and blueness study

The presence of veterinary drug residues in edible animal tissues endangers human health and safety, accordingly, global nations enacted legislative restrictions to monitor their concentrations in food. In this work, we introduce two fluorimetric sensors for determining nitroxynil (NXL), a crucial veterinary medication, in various matrices. Sensor I, novel nitrogen and sulfur-doped carbon quantum dots (S,N-CQDs), was fabricated from strawberry and leek juices as cheap and sustainable natural resources. Only five minutes of microwave radiation were required as a rapid synthesizing technique without any drastic conditions or organic solvents. The S,N-CQDs manifest blue emission using λex/em of 340/418 nm. The synthesized nanosensor was characterized using UV Spectroscopy, transmission electron microscopy (TEM), and Fourier-transform infrared spectrometry (FTIR). Sensor II was the acriflavine reagent (AV) that exhibits native fluorescence using λex/em of 265/505 nm. Both sensors displayed quantitative turning off in their native fluorescence by increasing concentrations of NXL (1.0–10.0 and 0.5–8.0 µg mL−1) with correlation coefficients r = 0.9998 and 0.9999 for sensors I and II, respectively. The two probes achieved satisfactory percentage recoveries and standard deviation (SD < 4) for NXL assessing in complex matrices of diverse food samples (bovine muscle, kidney, and fat) and Fasciolar® veterinary formulation. Additionally, they have been successfully used to detect the investigated drug in river ecosystems with a mean %recovery of 100.10 ± 1.70, and 99.95 ± 1.31 for sensors I and II, respectively. The two constructed sensors’ specificity has been confirmed for all tested matrices reflecting their feasibility as promising platforms in therapeutic drug monitoring, livestock ecosystems, food safety assurance, quality control of drugs, and environmental pollution monitoring. Quenching mechanisms for both methodologies were studied and the reaction stoichiometry for NXL − AV complex was calculated in two ways. Lastly, a comprehensive comparison was performed between the suggested methodologies and published fluorimetric works. The greenness feature was assessed by the Analytical Eco-scale (AES), Green Analytical Procedure Index (GAPI), and Analytical GREEnness Metric Approach (AGREE). In addition, white analytical chemistry principles were checked to assess sustainability criteria using the RGB 12 algorithm. The recently launched Blue Applicability Grade Index (BAGI) metric tool was also employed to assess the practicality (Blueness) character.

Calcium-Based Metal-Organic Framework: Detection and Idiosyncratic Removal of Copper by Nano-Particle Deposition.

A novel calcium-based metal-organic framework (CaMOF@LSB) was designed and synthesized, exhibiting dual functionality for both selective detection and removal of Cu2+ ions from aqueous solutions. The framework's stability, including solvent and pH variations, was established with notable thermal resilience. Colorimetric Cu2+ detection (≥5 ppm) with a high capture capacity of 484.2 mg g-1 by CaMOF@LSB places this material among the few that ensure efficient colorimetric detection and high removal capabilities of Cu2+ ions. Batch adsorption experiments revealed pH-dependent behavior and competitive interactions. Langmuir and pseudo-second-order kinetics models aptly described adsorption isotherms and kinetics, respectively. Thermodynamic assessments confirmed spontaneous and endothermic adsorption. Mechanistically, nanoparticle deposition contributes to the Cu2+ uptake. CaMOF@LSB also exhibited one of the best removal behaviour of Cu2+ by means of oxide formation on the surface. Regeneration of CaMOF@LSB was achieved by simple sonication in 0.1 M aqueous NaOH solution. The recyclability was also tested up to 5 cycles, and it exhibited a small decrease in adsorption capacity observed across the cycles. This research presents a promising avenue for addressing heavy metal pollution using metal-organic frameworks, thereby offering potential applications in water purification and environmental pollution monitoring and remediation.

Progress of Ecological Environment Research in Mining Areas based on Remote Sensing Technology

Significant progress has been made in the application of remote sensing technology in the study of ecological environment in mining areas. Using technologies such as hyperspectral remote sensing, multispectral remote sensing, low-altitude remote sensing by unmanned aerial vehicles and the construction of monitoring indicator systems, it has been widely applied to mine development and land use, monitoring of vegetation cover in mines, monitoring of the geological and hydrological environment in mines and monitoring of environmental pollution in mines. In the future, with the continuous emergence of new technologies and the optimization of remote sensing technology, the application of remote sensing technology in the monitoring and protection of mining ecological environment will be more extensive and in-depth, which can provide stronger support for mining ecological environment protection and sustainable development.

Monitoring of environmental persistent organic pollutants in hair samples of cats and dogs

This study investigated 32 persistent organic pollutants, including 9 organochlorine pesticides, 15 polychlorinated biphenyls, 6 polycyclic aromatic hydrocarbons, and 2 organophosphate pesticides in the hair samples of domestic cats and dogs living in an urban area in Samsun, Turkiye. Hair samples were collected from 35 cats and 38 dogs, grouped by sex and age (<3 or >3 years old). Samples were extracted using a liquid-liquid extraction method and analyzed by Gas Chromatography-Mass Spectrometry (GC–MS). The results revealed the presence of organochlorine pesticides (n = 58, 468.65 ± 92.30 ng/g), polycyclic aromatic hydrocarbons (n = 57, 15.65 ± 3.91 ng/g), polychlorinated biphenyls (n = 55, 54.11 ± 9.47 ng/g), and organophosphate pesticides (n = 25, 568.43 ± 113.17 ng/g) in the samples. PCBs 81, 118, 128, 208, and 2,4-DDE were not detected in any samples. Only one sample did not contain any of the searched compounds. Fluorene was the most frequently detected pollutant (n = 53, 72.6 %), followed by β-hexachlorocyclohexane (n = 34, 46.6 %). The highest maximum concentration was observed for hexachlorobenzene (2748.03 ng/g), followed by aldrin (2313.45 ng/g) and fenitrothion (2081.13 ng/g). Pollutant concentrations did not differ between cats and dogs, sexes, and ages (p > 0.05). This study highlights the significant threat that urban areas pose to pets, and therefore, POPs should be monitored periodically in hair and other samples. To the best of our knowledge, this is the first report to investigate POP levels in hair samples from cats and dogs in Turkiye.

Exploring the potential of eco-friendly carbon dots in monitoring and remediation of environmental pollutants.

Photoluminescent carbon dots (CDs) have garnered significant interest owing to their distinctive optical and electronic properties. In contrast to semiconductor quantum dots, which incorporated toxic elements in their composition, CDs have emerged as a promising alternative, rendering them suitable for both environmental and biological applications. CDs exhibit astonishing features, including photoluminescence, charge transfer, quantum confinement effect, and biocompatibility. Recently, CDs derived from green sources have drawn a lot of attention due to their strong photostability, reduced toxicity, better biocompatibility, enhanced fluorescence, and simplicity. These attributes have shown great promise in the areas of LED technology, bioimaging, photocatalysis, drug delivery, biosensing, and antibacterial activity. In contrast, this review offers a comprehensive overview of various green sources utilized to produce CDs and methodologies, along with their merits and demerits, with a notable emphasis on physiochemical properties. Additionally, the paper provides insight into the bibliometric analysis and recent advancements of CDs in sensing, photocatalysis, and antibacterial activity. In this field, extensive research is underway, and a total of 7,438 articles have been identified. Among these, 4242 articles are dedicated to sensing applications, while 1518 and 1678 focus on adsorption and degradation. Carbon dots demonstrate exceptional sensing capabilities within the nanomolar range with a selectivity of up to 95% for pollutants. They exhibit excellent degradation efficiency exceeding 90% within 10-130 min and possess an adsorption capacity from 100 to 800 mg/g. These fascinating qualities render them suitable for diverse applications.

Plasmon AgNPs/MoS2/ZnO nanorods array ternary heterojunctions enabling high-efficiency solar-light energy utilization for photocatalysis and recyclable SERS detection

BackgroundSurface-enhanced Raman scattering (SERS) has gained widespread use in molecule-level detection benefiting from its high sensitivity, nondestructive data acquisition, and capacity for providing molecular fingerprint information. However, the strong adhesion of target molecules to the substrate (known as the “memory effect”) inherently hinders the reusability of SERS substrates. Research has shown that self-cleaning SERS substrates based on versatile semiconductor materials with SERS enhancement capabilities and solar photocatalytic properties offer an effective platform for the sensitive detection and degradation of harmful molecules. ResultsIn this research, a resuable SERS-active substrate was facilely fabricated by anchoring silver nanoparticles (AgNPs) to the edges of MoS2 nanosheet decorated on ZnO nanorod arrays (NRAs). This innovative design exhibited a remarkable SERS enhancement factor (EF) of 4.6 × 107 and demonstrated significant solar photocatalytic efficiency. Such superior characteristics of ternary plasma heterojunction were ascribable to the synergistic effect of the “Schottky barrier” and “hot spots” between MoS2 and AgNPs, the inherent chemical enhancement proficiency of the MoS2/ZnO NRAs heterojunction, as well as the ultrafast electron transfer within the ternary heterojunction. SignificanceThe developed ternary heterojunction substrate enabled highly sensitive SERS detection of trace amounts of organic molecules. Moreover, this SERS substrate exhibited self-cleaning and recyclability via solar-light-driven photocatalysis. This bifunctional recyclable SERS substrate proved capable of meeting various requirements for routine monitoring of environmental organic pollutants and provided a robust avenue for advancing energy utilization materials that serve as high-performance SERS sensors and catalysts.

GIS platform ecological water environment pollution automatic monitoring and analysis

This paper summarizes the application of GIS platform for automatic monitoring of ecological water environmental pollution. Firstly, the function of GIS platform and its combination with environmental monitoring are briefly introduced, and then the pollution status of ecological water environment is analyzed, including the source of pollution, classification and the impact on environment and human beings. This paper focuses on the application of GIS in data collection and integration, spatial distribution analysis of pollutants, simulation and prediction of pollution diffusion, design and implementation of monitoring system, etc. Through the introduction of GIS technology, the monitoring and management of ecological water environmental pollution can be realized more effectively, which provides a strong support for environmental protection.

Confinement Enrichment Effect in HoMS-BaTiO3 Microwave Gas Sensors for the Detection of 10 ppb-0.55 v/v% Ammonia at Room Temperature.

The construction of ammonia gas sensors with wide detection ranges is important for exhalation diagnosis and environmental pollution monitoring. To achieve a wide detection range, sensitive materials must possess excellent spatial confinement and large active surfaces to enhance gas adsorption. In this study, an ammonia microwave gas sensor with a wide detection range of 10 ppb-0.55 v/v% at room temperature was fabricated by incorporating hollow multishelled-structured BaTiO3 (HoMS-BaTiO3). The effect of the number of shells and the quantity of the sensitive material on the gas-sensing performance was investigated, and two-layered HoMS-BaTiO3 demonstrated the best response at high concentrations (0.15-0.55 v/v%). Conversely, single-layered HoMS-BaTiO3 displayed outstanding performance at low concentrations (10 ppb-0.15 v/v%). The lower the quantity of the sensitive material, the higher the response. This study offers a method for preparing room-temperature ammonia sensors with a wide detection range and reveals the link between the structure and quantity of sensitive materials and gas-sensing performance.

Biomass Combustion in Boiler: Environmental Monitoring of Sugar Markers and Pollutants

The need to use renewable sources and matrices with energy potential is widely recognized. The development of innovative technologies aimed at the improvement of energy conversion processes and reducing environmental impacts is currently receiving increasing attention from the scientific community and policymakers. The presence of sugars in airborne particle materials is attributed to biomass combustion. For this reason, these compounds are considered markers of biomass burning. The purpose of this work was to evaluate the emissions produced by agroforestry biomass burning (citrus pruning) by simultaneously sampling both stack emissions and atmospheric particulates in the area around a biomass boiler to understand the real contribution of biomass burning to atmospheric pollution. The combustion tests were carried out by comparing the processes with and without particulate abatement system to see how biomass combustion’s contribution to particulate emission can be controlled and reduced. During the tests, the focus was on particulate matter (PM) speciation in terms of sugar marker identification and determination. This study aims to increase knowledge to better understand the contribution of biomass plants to air pollution and differentiate it from the contributions of other sources, such as vehicular traffic or domestic heating.

Development of a trend forecasting model for environmental pollution monitoring

A complex model for forecasting time series of environmental pollution indicators is described, considering the aggregation of various forecasting models, which are formed based on predictive statistical analysis of pollution indicators and have an adaptive nature. The model differs from known models by providing the possibility of adapting the model parameters to changes in the state of the environment, which is especially important in the conditions of using such models in monitoring systems. Th e complex forecasting model includes higher-order exponential smoothing, Holt, Winters, moving average, weighted moving average, and autoregression models. All the parameters set in these models are related to the Hurst index, which is calculated based on predictive fractal statistical analysis of the time series. Relevant descriptions and justifications are given. Using such a model as part of the econometric system will help predict and respond more effectively to possible changes in the values of pollution parameters. In particular, the persistence of the time series of pollution parameters can mean a stable trend of increasing or decreasing pollution. Suppose the time series becomes close to random or ergodic. In that case, this may mean an emergency or additional erratic emissions in the region that must be monitored. The described model is a forecasting model that is part of the system for monitoring environmental pollution parameters. In the future, a model for forecasting the pollution level in different regions of the People's Republic of China will be implemented.

Extremozyme-Based Biosensors for Environmental Pollution Monitoring: Recent Developments.

Extremozymes combine high specificity and sensitivity with the ability to withstand extreme operational conditions. This work presents an overview of extremozymes that show potential for environmental monitoring devices and outlines the latest advances in biosensors utilizing these unique molecules. The characteristics of various extremozymes described so far are presented, underlining their stability and operational conditions that make them attractive for biosensing. The biosensor design is discussed based on the detection of photosynthesis-inhibiting herbicides as a case study. Several biosensors for the detection of pesticides, heavy metals, and phenols are presented in more detail to highlight interesting substrate specificity, applications or immobilization methods. Compared to mesophilic enzymes, the integration of extremozymes in biosensors faces additional challenges related to lower availability and high production costs. The use of extremozymes in biosensing does not parallel their success in industrial applications. In recent years, the "collection" of recognition elements was enriched by extremozymes with interesting selectivity and by thermostable chimeras. The perspectives for biosensor development are exciting, considering also the progress in genetic editing for the oriented immobilization of enzymes, efficient folding, and better electron transport. Stability, production costs and immobilization at sensing interfaces must be improved to encourage wider applications of extremozymes in biosensors.

Hierarchical CoWO4/NixFeyS microspheres bearing crystalline-amorphous interface as a multifunctional platform for outperformed water splitting and sensitive hydrazine sensing

Highly efficient and multifunctional electrocatalysts are of high value in energy transformation and electrochemical sensing. Herein, hierarchically architectured cobalt tungstate/nickel iron sulfide (CoWO4/NixFeyS) microspheres with a crystalline-amorphous interface have been prepared on bimetallic substrate of nickel–iron foam (NIF) by a two-step hydrothermal method. Electrochemical characterization shows that CoWO4/NixFeyS microspheres can boost the electrocatalytic activity effectively through the synergistic effect on the crystalline-amorphous interface. When the CoWO4/NixFeyS is applied as the electrocatalysts for oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER), the overpotentials at a high current density of 500 mA cm−2 are only 322.8 mV and 306.5 mV, respectively. The overall water splitting device composed of CoWO4/NixFeyS/NIF couple only needs a cell voltage of 1.80 V to reach a current density of 100 mA cm−2, and 2.19 V to reach 500 mA cm−2. The CoWO4/NixFeyS/NIF can be also utilized as an effective electrochemical platform for the sensing of toxic hydrazine in a wide range from 50 μM to 17.3 mM, with a detection limit of 46.4 μM. All these results display that the CoWO4/NixFeyS/NIF can be a high-performance multifunctional material for energy transformation and environmental pollutant monitoring.

Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management

Detecting hazardous substances in the environment is crucial for protecting human wellbeing and ecosystems. As technology continues to advance, artificial intelligence (AI) has emerged as a promising tool for creating sensors that can effectively detect and analyze these hazardous substances. The increasing advancements in information technology have led to a growing interest in utilizing this technology for environmental pollution detection. AI-driven sensor systems, AI and Internet of Things (IoT) can be efficiently used for environmental monitoring, such as those for detecting air pollutants, water contaminants, and soil toxins. With the increasing concerns about the detrimental impact of legacy and emerging hazardous substances on ecosystems and human health, it is necessary to develop advanced monitoring systems that can efficiently detect, analyze, and respond to potential risks. Therefore, this review aims to explore recent advancements in using AI, sensors and IOTs for environmental pollution monitoring, taking into account the complexities of predicting and tracking pollution changes due to the dynamic nature of the environment. Integrating machine learning (ML) methods has the potential to revolutionize environmental science, but it also poses challenges. Important considerations include balancing model performance and interpretability, understanding ML model requirements, selecting appropriate models, and addressing concerns related to data sharing. Through examining these issues, this study seeks to highlight the latest trends in leveraging AI and IOT for environmental pollution monitoring.

A Three-Dimensional Hydrophobic Surface-Enhanced Raman Scattering Sensor via a Silver-Coated Polytetrafluoroethylene Membrane for the Direct Trace Detection of Molecules in Water.

We report a three-dimensional (3D) SERS substrate consisting of a silver nanoparticle (AgNP) coating on the skeleton-fiber surfaces of a polytetrafluoroethylene (PTFE) membrane. Simple thermal evaporation was employed to deposit Ag onto the PTFE membrane to produce grape-shaped AgNPs. The 3D-distributed AgNPs exhibit not only strong localized surface plasmon resonance (LSPR) but also strong hydrophobic performance. High-density hotspots via silver nano-grape structures and nanogaps, the large 3D interaction volume, and the large total surface area, in combination with the hydrophobic enrichment of the specimen, facilitate high-sensitivity sensing performance of such a SERS substrate for the direct detection of low-concentration molecules in water. An enhancement factor of up to 1.97 × 1010 was achieved in the direct detection of R6G molecules in water with a concentration of 10-13 mol/L. The lowest detection limit of 100 ppt was reached in the detection of melamine in water. Such a SERS sensor may have potential applications in food-safety control, environmental water pollution monitoring, and biomedical analysis.

ОРГАНИЗАЦИЯ ПОДВОДНОЙ БЕСПРОВОДНОЙ СИСТЕМЫ СВЯЗИ

The article discusses underwater wireless communication systems. Research in the field of underwater optical wireless communication system will allow developing science, industry, to find solutions to defense tasks and emergencies, to carry out remote monitoring of environmental pollution of the underwater world and control underwater objects and equipment of oilrigs, to conduct underwater research and much more. The purpose of the work is to develop a classification of the principles of construction and organization of underwater wireless communication, taking into account modern achievements and development of technologies in the field of underwater wireless communication systems, to assess the strengths and weaknesses of underwater acoustic, radio frequency and optical communication systems. It is shown that the underwater optical wireless communication system has a great potential to enhance the traditional underwater acoustic communication system and underwater radio frequency communication system due to the high speed of information transmission, low latency, lower power consumption and compact size. To select the equipment and organize the communication channel, a generalized classification of an underwater optical wireless communication system has been developed, depending on the routing protocols used, on the configuration of the communication channel, on the optical properties of water, on the type of water in which the transmission channel is organized, on the mobility of underwater vehicles and the coverage area, on the type of modulation used, the method of underwater communication and from the factors affecting the organization of the communication channel.

Wireless Sensor Networks for Green Cities: A Comprehensive Review of Environmental Pollution Monitoring

This research paper investigates the design and implementation of a Wireless Sensor Network (WSN)-Based Data Acquisition System tailored for collecting environmental pollution factors with a specific focus on contributing to the realization of a Green City. Leveraging various literature surveys on WSN and its applications with different techniques, a comprehensive analysis of the existing body of knowledge in the field. The paper explores the deployment of WSN technology as a cost-effective and scalable solution for real-time monitoring of pollution-related parameters, including air and water quality, noise levels, and other relevant environmental factors.By synthesizing insights from diverse literature sources, propose an intelligent and adaptable WSN framework capable of capturing, analyzing, and transmitting real-time environmental data. The research highlights the importance of integrating advanced sensor technologies within the WSN infrastructure to ensure a holistic monitoring of pollution factors. This analysis also delves into various data acquisition methodologies and explores the potential for advanced data analytics and visualization techniques to derive meaningful insights

Environmental pollution monitoring: Essential strategies for mitigating ecological degradation

Environmental pollution is a critical issue that threatens ecological balance and public health. This study focuses on essential strategies for monitoring environmental pollution to mitigate ecological degradation. The primary objective is to assess how sophisticated monitoring systems can enhance the detection and management of pollution sources. Advanced sensor networks and real-time data collection techniques are utilized to evaluate air and water quality, soil contamination, and other key environmental parameters. The methods involve deploying these technologies to provide comprehensive insights into pollution patterns, enabling timely data analysis. The results highlight the effectiveness of these monitoring systems in identifying pollution sources, detecting environmental violations early, and guiding policy decisions. The findings underscore the importance of integrating advanced monitoring technologies and methodologies to strengthen efforts in preserving ecological balance and protecting public health. This research contributes to the broader understanding of how enhanced monitoring can lead to more effective pollution control measures and sustainable environmental management.

Recent advances in nanomaterial-based solid-contact ion-selective electrodes.

Solid-contact ion-selective electrodes (SC-ISEs) are advanced potentiometric sensors with great capability to detect a wide range of ions for the monitoring of industrial processes and environmental pollutants, as well as the determination of electrolytes for clinical analysis. Over the past decades, the innovative design of ion-selective electrodes (ISEs), specifically SC-ISEs, to improve potential stability and miniaturization for in situ/real-time analysis, has attracted considerable interest. Recently, the utilisation of nanomaterials was particularly prominent in SC-ISEs due to their excellent physical and chemical properties. In this article, we review the recent applications of various types of nanostructured materials that are composed of carbon, metals and polymers for the development of SC-ISEs. The challenges and opportunities in this field, along with the prospects for future applications of nanomaterials in SC-ISEs are also discussed.

Material-specific binding peptides empower sustainable innovations in plant health, biocatalysis, medicine and microplastic quantification.

Material-binding peptides (MBPs) have emerged as a diverse and innovation-enabling class of peptides in applications such as plant-/human health, immobilization of catalysts, bioactive coatings, accelerated polymer degradation and analytics for micro-/nanoplastics quantification. Progress has been fuelled by recent advancements in protein engineering methodologies and advances in computational and analytical methodologies, which allow the design of, for instance, material-specific MBPs with fine-tuned binding strength for numerous demands in material science applications. A genetic or chemical conjugation of second (biological, chemical or physical property-changing) functionality to MBPs empowers the design of advanced (hybrid) materials, bioactive coatings and analytical tools. In this review, we provide a comprehensive overview comprising naturally occurring MBPs and their function in nature, binding properties of short man-made MBPs (<20 amino acids) mainly obtained from phage-display libraries, and medium-sized binding peptides (20-100 amino acids) that have been reported to bind to metals, polymers or other industrially produced materials. The goal of this review is to provide an in-depth understanding of molecular interactions between materials and material-specific binding peptides, and thereby empower the use of MBPs in material science applications. Protein engineering methodologies and selected examples to tailor MBPs toward applications in agriculture with a focus on plant health, biocatalysis, medicine and environmental monitoring serve as examples of the transformative power of MBPs for various industrial applications. An emphasis will be given to MBPs' role in detecting and quantifying microplastics in high throughput, distinguishing microplastics from other environmental particles, and thereby assisting to close an analytical gap in food safety and monitoring of environmental plastic pollution. In essence, this review aims to provide an overview among researchers from diverse disciplines in respect to material-(specific) binding of MBPs, protein engineering methodologies to tailor their properties to application demands, re-engineering for material science applications using MBPs, and thereby inspire researchers to employ MBPs in their research.