Mitigation Tool Research Articles

Reflections on the Consideration of Greenhouse Gas Emissions in Environmental Impact Assessment

Abstract Environmental impact assessment (EIA) involves assessing the implications of proposed activities on the environment to inform decisions about whether those actions should proceed and under what conditions. Efforts are being made to incorporate climate change considerations into EIA internationally, but the assessment of greenhouse gas (GHG) emissions poses particular challenges. This article compares the incorporation of GHG emissions into EIA in two jurisdictions: Canada (under the Impact Assessment Act 2019) and Western Australia (under the Environmental Protection Act 1986). Four questions are considered, relating to screening and scoping; information requirements; decision-making and condition setting; and post-approval activities. Key differences between the two jurisdictions were found in relation to screening and scoping (Western Australia applies an emissions threshold while Canada utilizes a project list coupled with tailored guidelines); decision-making (Western Australia generally considers a straight line trajectory to net zero by 2050 as acceptable whereas Canada considers emissions in the context of international commitments and against other sustainability considerations); and post-approval activities (a strength of the Western Australian system is mechanisms enabling review and tightening of GHG conditions over time). It will be important to continue to review the effectiveness of EIA as a tool for climate mitigation as practice evolves.

Managing Climate Risks and Adaptation in Coastal Communities: How to Provide Information

In recent years, climate adaptation has gained significant attention from policymakers and public managers. In the U.S., states play a crucial role in developing coastal management policies, initiatives, and programs to reduce climate risks and enhance protection against extreme weather. Despite various approaches, few studies have examined information provision tools for coastal hazard mitigation and climate adaptation. As a result, there is limited knowledge about effective adaptation tools with low transaction costs. Using the StormSmart Coasts program as a case study, this research explores information-based climate adaptation and the components needed for a successful information-sharing platform. Established by the Massachusetts Office of Coastal Zone Management in 2008, StormSmart Coasts is a web-based program offering practical information for hazard mitigation to local decision-makers and communities. The study identifies three key features of an effective tool: providing tailored information to different stakeholders, serving as an outreach tool, and connecting with diverse stakeholders, including local managers and homeowners. The findings suggest that a well-designed information-sharing tool can enhance adaptive capacity and improve climate change preparedness in coastal communities.

Pendampingan Analisis Kelayakan Sosial Pasar Tradisional Landungsari

The market is a collection of all buyers and sellers interacting socially in selling and purchasing goods. The existence of markets, especially traditional markets, supports economic activities that can contribute to the economic growth of the surrounding community. The traditional market is the center of buying and selling transactions directly in the community. One of its functions is as a center for the socio-economic activities of the local community. The traditional market of Landungsari Village is an economic forum for the Landungsari community in buying and selling transactions between buyers and sellers. Market development must adjust to the development of the surrounding community. The problem in the traditional market of Landungsari Village is that there is no social feasibility study in developing and realigning the Landungsari Market in the surrounding community. The service aims to solve the problems by conducting a social feasibility study survey of the development and improvement plan and realignment of the Landungsari Market. In its implementation, the service team partnered with the Landungsari Market Manager and the Landungsari Village Government. The result of the service was that 76% of the subjects expected an improvement in the cleanliness of the Landungsari Market, and 100% of the subjects also expected the provision of evacuation routes, symbols, and disaster mitigation tools.

Mitigation of Karenia brevis Cells and Brevetoxins Using Curcumin, a Natural Supplement

Curcumin, a natural plant product, was investigated as a mitigation tool against Karenia brevis, the toxic dinoflagellate responsible for Florida red tides. A series of laboratory bench-top studies were conducted with additions of 0.1, 1, 2, 3, 5, 10, 20, 30, and 40 mg/L curcumin to K. brevis at an average of 1.0 × 106 cells/L to determine the efficacy of curcumin against K. brevis cells and brevetoxins and to optimize treatment dosage. Treatment with 5 mg/L of curcumin reduced K. brevis cell abundance by 89% and total brevetoxins by 60% within 24 h. Lower concentrations of curcumin (0.1–3 mg/L) exhibited between a 2 and 45% reduction in K. brevis and a reduction in brevetoxins of between 2 and 44% within 24 h. At the highest curcumin doses, 30 and 40 mg/L, a 100% reduction in cell abundance was observed by 6 h, with reduction in total brevetoxins by at least 64% in 48 h. These results suggest that curcumin, used alone or potentially in combination with other technologies, is a promising K. brevis bloom mitigation option.

Short term forecasting of base metals prices using a LightGBM and a LightGBM - ARIMA ensemble

AbstractBase metals are key materials for various industrial sectors such as electronics, construction, manufacturing, etc. Their selling price is important both for the profitability of the mining and metallurgical companies that produce and trade them, as well as for the countries whose economies rely on their exports or tax revenues as a means for national income. Prices are also critical for companies that use base metals as inputs to fabricate end products. The prediction of prices’ future movements can serve as a tool for risk mitigation and better budget planning. In this study, the logarithmic returns of base metals are forecasted using an autoregressive Light Gradient Boosting Machine (LightGBM) as well as an ensemble comprising the aforementioned algorithm and a classical time series forecasting model (i.e., ARIMA). The two models are then compared to three simpler benchmark models, namely a global mean model, an exponential smoothing model and an ARIMA model. When comparing using RMSE, the autoregressive LightGBM model outperformed the three univariate benchmark models (and the ensemble) for forecasting 6 months ahead for aluminum and nickel returns, while copper and zinc returns were forecasted better by the ensemble. Neither of the proposed models performed better than an ARIMA model when it comes to forecasting lead and tin returns.

Study on Bamboo Industry

Abstract: The article highlights bamboo as a versatile material with numerous applications across various industries. Its widespread availability, rapid growth, and favorable physical and chemical properties make it a convenient and easily accessible resource globally. Bamboo, being one of the oldest traditional building materials, has a rich history of use in construction. Bamboo belongs to the grass family and is renowned for being the fastest-growing plant inthe world. Its industrial applications span a wide range, including food production, wood substitute, pulp and paper production, medicinal products, cottage industries, and charcoal production The Indian bamboo market is anticipated to experience significant growth in the forecast period. The increasing demand for furniture, driven by the rise in per capita income among consumers in the country, is expected to contribute to the market's expansion. Bamboo's ability to thrive on otherwisemarginal lands makes it a profitable crop for cultivation in degraded areas. Additionally, its rapid growth makes bamboo an effective tool for climate change mitigation and carbon sequestration, with the capacity to absorb substantial amounts of carbon per hectare In summary, the article underscores bamboo's potential as a sustainable and environmentally friendly material with diverse applications across industries. It also emphasizes its role in addressing climate change and contributing to carbon sequestration, positioning bamboo as a valuable resource for both economic and ecological purposes

Research and application of a flexible measuring array for deep displacement of landslides

Abstract. The multidimensional and multi-sliding surface measurement of deep-seated displacement on landslides poses a significant technical challenge in landslide monitoring and early warning. The fixed-borehole inclinometer serves as an important measurement method based on drilling for this purpose. In this study, a novel flexible measurement array for deep-seated landslide displacement and its installation and measurement processes were developed, enabling higher accuracy in full-hole multidimensional deformation measurement. The measurement array consists of individual measurement probes as basic units, connected in series through coaxial cables and high-pressure rubber hoses, forming a flexible measurement array. Each probe is equipped with acceleration and magnetic field sensors, allowing for the measurement of borehole inclination and azimuth angles and providing a more comprehensive understanding of the deformation of deep-seated landslides. This flexible measurement array resolves the limitations of traditional fixed inclinometers, such as limited probe quantity or inaccurate installation positions that fail to reflect the deformation trend of the landslide body. Moreover, it eliminates the need for auxiliary installation accessories like pulleys and inclinometer pipes, simplifying the mechanical structure and installation process, which represents an advancement in methodology and an improvement in measurement techniques. This array provides a more comprehensive and improved monitoring tool for disaster prevention and mitigation, thereby enhancing the level of geological hazard monitoring and early warning technology.

Global habitat predictions to inform spatiotemporal fisheries management: Initial steps within the framework

Tuna Regional Fishery Management Organizations (tRFMOs) are increasingly interested in spatiotemporal management as a tool to reduce interaction rates with vulnerable species. We use blue shark (Prionace glauca) as a case study to demonstrate the critical first steps in the implementation process, highlighting how predictions of global habitat for vulnerable life stages can be transformed into a publicly-accessible spatial bycatch mitigation tool. By providing examples of possible management goals and an associated threshold to identify essential habitats, we show how these key areas can represent a relatively low percentage of oceanic area on a monthly basis (16–24% between 50°S and 60°N), yet can have relatively high potential protection efficiency (∼ 42%) for vulnerable stages if fishing effort is redistributed elsewhere. While spatiotemporal management has demonstrable potential for blue sharks to effectively mitigate fishing mortality on sensitive life stages, we identify inherent challenges and sequential steps that require careful consideration by tRFMOs as work proceeds. We also discuss how our single-species framework could be easily extended to a multispecies approach by assigning relative conservation risk before layering habitat model predictions in an integrated analysis. Such broader application of our approach could address the goals of tRFMOs related to reducing the ecosystem effects of fishing and pave the way for efficient fisheries co-management using an ecosystem-based approach.

A Review of Code Obfuscation and Anti Analysis Techniques

This paper investigates the intricate landscape of code obfuscation and anti analysis techniques within software security. The primary objective is to comprehensively understand the various methods employed to obscure code functionality and impede analysis efforts. Through an extensive literature review, this study examines the fundamental concepts of code obfuscation and identifies common anti analysis strategies utilized by malware authors. By exploring the arms race between obfuscation and analysis, this paper aims to shed light on the evolving tactics employed by both defenders and adversaries in cybersecurity. Methodologically, this research delves into the detailed explanation of prevalent code obfuscation techniques, including control flow obfuscation, data obfuscation, and string obfuscation, alongside examples and case studies illustrating their effectiveness. Similarly, the study scrutinizes anti analysis methods utilized by malware authors, highlighting their impact on software security and malware analysis. Through experimental evaluation and case studies of real world incidents, this research evaluates the efficacy of code obfuscation and anti analysis techniques, providing insights into their implications for software security and malware defence strategies. Key findings of this research underscore the critical role of code obfuscation in software security and the escalating challenge it poses for malware detection and analysis. Moreover, the study elucidates the significance of effectively understanding and countering anti analysis techniques to bolster cybersecurity defences. The implications of this research extend to practitioners and researchers, offering valuable insights into developing mitigation strategies and tools to combat code obfuscated malware and enhance overall software security.

Exploring Biochar with N-Fertilizer Effects on Soil CO2 Emissions and Physical-Chemical Properties as a Climate Change Mitigation Tool

Abstract The global agriculture industry is facing never before faced issues in the form of soil degradation, water scarcity, rising greenhouse gas emissions, and climate change. Among the possible remedies, applying biochar to the soil has drawn interest as a viable strategy. Although a great deal of literature has been written about the benefits and drawbacks of applying biochar initially, there is still a significant amount of research on the effects of using biochar repeatedly. This study seeks to address this gap by examining the varied effects of both the initial application (at rates of 0 t.ha−1, 10 t.ha−1, and 20 t.ha−1) and the reapplication of biochar (at rates of 0, 10, and 20 t.ha−1), especially when combined with different levels of nitrogen fertilizer (0, 108, and 162 kg.ha−1). The investigation focuses on soil properties and CO2 emissions from Haplic Luvisol in the temperate climate zone (Slovakia). The results showed that biochar generally improved soil properties, such as soil pH (KCl) (p <0.05), shifting it from acidic towards moderately acidic, and generally led to a decrease in ammonium (NH4 +) and nitrate (NO3 -) content. The second level of fertilization, combined with different biochar treatments, yielded the most efficient results in physical properties such as soil temperature, bulk density (BD), and soil water content (SWC) compared to control treatments without biochar. Biochar application contributed to the reduction of both average daily CO2 emissions and cumulative CO2 emissions during the study period (April – October) in 2022 compared to the control without biochar application.

Improving Employee Safety Through a Comprehensive Patient Behavioral Program.

Health care workers in the United States are facing increasing rates of exposure to aggressive behavior, resulting in an increase in employee injuries related specifically to patient behavioral events. By leveraging interprofessional collaboration and system-level innovation, we aimed to reduce the rate of employee injuries related to patient behavioral events at a children's hospital by 50% over a 3-year period. An interdisciplinary quality improvement team comprising physicians, behavior analysts, nursing, and other key stakeholders developed a comprehensive behavior program in our children's hospital. The team developed 5 key pillars: aggression mitigation tools, clinical resources, advanced training, screening and management, and behavior emergency response. The outcome measure was rate of reported employee safety events related to patient behavioral events. This was tracked via prospective time series analysis statistical process control chart using established rules to detect special cause variation. The average rate of employee injuries resulting from patient behavioral events decreased from 0.96 to 0.39 per 1000 adjusted patient-days, with special cause variation observed on a statistical process control U-chart. This improvement has been sustained for 16 months. Staff members who experienced injuries included nurses and patient technicians, with common antecedents to injuries including medical interventions or patient requests that could not be safely met. A unified and multimodal system aimed to address pediatric patient behavioral events can reduce employee injuries and foster a culture of employee safety in the pediatric inpatient setting.

Practical guidelines for eating disorder risk mitigation in patients undergoing obesity treatment for the pediatric provider.

Pediatric obesity is a growing concern globally. Patients with a history of overweight/obesity often experience stigmatization, especially in the healthcare setting, and are at increased risk of developing psychological comorbidities including eating disorders. This review appraises the most recent studies evaluating eating disorder risk in youth undergoing treatment for obesity, identifies gaps in the literature, and offers practical guidelines to pediatric providers regarding the management of this population. Recent studies suggest that structured weight management programs may decrease the risk of and/or improve symptoms of certain eating disorders such as binge eating disorder and bulimia nervosa. There is a paucity of research on some components of obesity management such as obesity pharmacotherapeutics and eating disorder risk. Children and adolescents with obesity are a psychologically vulnerable population with increased risk for the development of eating disorders. Further study is needed to evaluate general risk in the setting of specialized and primary care obesity interventions and develop appropriate screening and mitigation tools. Some evidence-based strategies can aid pediatric providers in both weight management and eating disorder prevention and risk assessment.

Create the Taxonomy for Unintentional Insider Threat via Text Mining and Hierarchical Clustering Analysis

The unintentional activities of system users can jeopardize the confidentiality, integrity, and assurance of data on information systems. These activities, known as unintentional insider threat activities, account for a significant percentage of data breaches. A method to mitigate or prevent this threat is using smart systems or artificial intelligence (AI). The construction of an AI requires the development of a taxonomy of activities. The literature review focused on data breach threats, mitigation tools, taxonomy usage in cybersecurity, and taxonomy development using Endnote and Google Scholar. This study aims to develop a taxonomy of unintentional insider threat activities based on narrative descriptions of the breach events in public data breach databases. The public databases were from the California Department of Justice, US Health and Human Services, and Verizon, resulting in 1850 examples of human errors. A taxonomy was constructed to specify the dimensions and characteristics of objects. Text mining and hierarchical cluster analysis were used to create the taxonomy, indicating a quantitative approach. Ward’s agglomeration coefficient was used to ensure the cluster was valid. The resulting top-level taxonomy categories are application errors, communication errors, inappropriate data permissions, lost media, and misconfigurations.

‘Dead birds flying': can north American rehabilitated raptors released into the wild mitigate anthropogenic mortality?

As the human footprint expands to meet societal energy needs, as do the impacts to wildlife. Raptors in particular are highly susceptible to anthropogenic caused mortality. Industry sectors are encouraged to offset these causes of mortality. Several options to mitigate these losses have been proposed, including raptor rehabilitation. However, its role as a conservation tool is untested. Currently no peer‐reviewed demographic analyses exist using post‐release data from rehabilitated raptors to evaluate its effectiveness at continental scales. Our objectives were to estimate annual survival of rehabilitated and wild raptors, and then use those estimates in demographic models to assess potential effects at individual and population levels. We hypothesized that rehabilitated raptors would survive similarly to their wild counterparts after an acclimation period, and that longer‐lived species (K‐selected) would benefit most from these releases. We used US Geological Survey Bird Banding Lab band‐recovery data (1974–2018) from 20 raptor species for modeling survival of rehabilitated individuals (n = 125 740) in comparison to wild birds (n = 1 913 352). Results from 17 species with adequate recovery data indicated that five species rehabilitated ≠ wild survival, two species had uncertain estimates, and 10 species rehabilitated ≈ wild survival by years two and three post‐release. We acquired admission (n = 69 707) and release (n = 25 740) data from 24 rehabilitation centers across the US (2012–2021). We integrated survival, fecundity and numbers of releases into demographic models. These models quantified the extent to which rehabilitated raptors may contribute to broader conservation efforts, especially in the context of individual take. All but two species, had measurable numbers of individuals added to the population regardless of the number of releases. The general pattern was for K‐selected species to yield larger benefits from rehabilitated supplementation to the population. These results provide evidence that rehabilitation may serve as mitigation tool to offset incidental take.

How territoriality and sociality influence the habitat selection and movements of a large carnivore.

While territoriality is one of the key mechanisms influencing carnivore space use, most studies quantify resource selection and movement in the absence of conspecific influence or territorial structure. Our analysis incorporated social information in a resource selection framework to investigate mechanisms of territoriality and intra-specific competition on the habitat selection of a large, social carnivore. We fit integrated step selection functions to 3-h GPS data from 12 collared African wild dog packs in the Okavango Delta and estimated selection coefficients using a conditional Poisson likelihood with random effects. Packs selected for their neighbors' 30-day boundary (defined as their 95% kernel density estimate) and for their own 90-day core (defined as their 50% kernel density estimate). Neighbors' 30-day boundary had a greater influence on resource selection than any habitat feature. Habitat selection differed when they were within versus beyond their neighbors' 30-day boundary. Pack size, pack tenure, pup presence, and seasonality all mediated how packs responded to neighbors' space use, and seasonal dynamics altered the strength of residency. While newly-formed packs and packs with pups avoided their neighbors' boundary, older packs and those without pups selected for it. Packs also selected for the boundary of larger neighboring packs more strongly than that of smaller ones. Social structure within packs has implications for how they interact with conspecifics, and therefore how they are distributed across the landscape. Future research should continue to investigate how territorial processes are mediated by social dynamics and, in turn, how territorial structure mediates resource selection and movement. These results could inform the development of a human-wildlife conflict (HWC) mitigation tool by co-opting the mechanisms of conspecific interactions to manage space use of endangered carnivores.

Mitigating animal methods bias to reduce animal use and improve biomedical translation.

Nonanimal biomedical research methods have advanced rapidly over the last decade making them the first-choice model for many researchers due to improved translatability and avoidance of ethical concerns. Yet confidence in novel nonanimal methods is still being established and they remain a small portion of nonclinical biomedical research, which can lead peer reviewers to evaluate animal-free studies or grant proposals in a biased manner. This "animal methods bias" is the preference for animal-based research methods where they are not necessary or where nonanimal-based methods are suitable. It affects the fair consideration of animal-free biomedical research, hampering the uptake and dissemination of these approaches by putting pressure on researchers to conduct animal experiments and potentially perpetuating the use of poorly translatable model systems. An international team of researchers and advocates called the Coalition to Illuminate and Address Animal Methods Bias (COLAAB) aims to provide concrete evidence of the existence and consequences of this bias and to develop and implement solutions towards overcoming it. The COLAAB recently developed the first of several mitigation tools: the Author Guide for Addressing Animal Methods Bias in Publishing, which is described herein along with broader implications and future directions of this work.

A 1D CNN-Based Emulator of CMAQ: Predicting NO2 Concentration over the Most Populated Urban Regions in Texas

Abstract In this study, we developed an emulator of the Community Multiscale Air Quality (CMAQ) model by employing a one-dimensional (1D) convolutional neural network (CNN) algorithm to predict hourly surface nitrogen dioxide (NO2) concentrations over the most densely populated urban regions in Texas. The inputs for the emulator were the same as those for the CMAQ model, which includes emission, meteorological, and land-use/land-cover data. We trained the model over June, July, and August (JJA) of 2011 and 2014 and then tested it on JJA of 2017, achieving an index of agreement (IOA) of 0.95 and a correlation of 0.90. We also employed temporal threefold cross validation to evaluate the model’s performance, ensuring the robustness and generalizability of the results. To gain deeper insights and understand the factors influencing the model’s surface NO2 predictions, we conducted a Shapley additive explanations analysis. The results revealed solar radiation reaching the surface, planetary boundary layer height, and NOx (NO + NO2) emissions are key variables driving the model’s predictions. These findings highlight the emulator’s ability to capture the individual impact of each variable on the model’s NO2 predictions. Furthermore, our emulator outperformed the CMAQ model in terms of computational efficiency, being more than 900 times as fast in predicting NO2 concentrations, enabling the rapid assessment of various pollution management scenarios. This work offers a valuable resource for air pollution mitigation efforts, not just in Texas, but with appropriate regional data training, its utility could be extended to other regions and pollutants as well. Significance Statement This work develops an emulator of the Community Multiscale Air Quality model, using a one-dimensional convolutional neural network to predict hourly surface NO2 concentrations across densely populated regions in Texas. Our emulator is capable of providing rapid and highly accurate NO2 estimates, enabling it to model diverse scenarios and facilitating informed decision-making to improve public health outcomes. Notably, this model outperforms traditional methods in computational efficiency, making it a robust, time-efficient tool for air pollution mitigation efforts. The findings suggest that key variables like solar radiation, planetary boundary layer height, and NOx (NO + NO2) emissions significantly influence the model’s NO2 predictions. By adding appropriate training data, this work can be extended to other regions and other pollutants such as O3, PM2.5, and PM10, offering a powerful tool for pollution mitigation and public health improvement efforts worldwide.

Structure of Aspergillus flavus populations associated with maize in Greece, Spain, and Serbia: Implications for aflatoxin biocontrol on a regional scale.

Aspergillus flavus is the most frequently identified producer of aflatoxins. Non-aflatoxigenic members of the A. flavus L strains are used in various continents as active ingredients of bioprotectants directed at preventing aflatoxin contamination by competitive displacement of aflatoxin producers. The current research examined the genetic diversity of A. flavus L strain across southern Europe to gain insights into the population structure and evolution of this species and to evaluate the prevalence of genotypes closely related to MUCL54911, the active ingredient of AF-X1. A total of 2173L strain isolates recovered from maize collected across Greece, Spain, and Serbia in 2020 and 2021 were subjected to simple sequence repeat (SSR) genotyping. The analysis revealed high diversity within and among countries and dozens of haplotypes shared. Linkage disequilibrium analysis indicated asexual reproduction and clonal evolution of A. flavus L strain resident in Europe. Moreover, haplotypes closely related to MUCL54911 were found to belong to the same vegetative compatibility group (VCG) IT006 and were relatively common in all three countries. The results indicate that IT006 is endemic to southern Europe and may be utilized as an aflatoxin mitigation tool for maize across the region without concern for potential adverse impacts associated with the introduction of an exotic microorganism.

Landslide Susceptibility Assessment in Nuwakot: An Examination of Methods to Mapping

The highest re-occurring hazard incident in Nepal in 2022 is reported to be fi re and landslides. A comprehensive study on understanding and identifying landslide susceptible areas and planning accordingly is perhaps one approach to disaster preparedness. In this context, landslide susceptibility assessment (LSA), plays a key role as a preparedness and mitigation tool at the local level. Landslide susceptibility, theoretically, denotes a geographic location of potential reoccurrence of landslide in an area based on several causative factors. I have conducted this study to explore landslide occurrence in Nepal based on secondary data, and map landslide susceptibility in Nuwakot district by using spatial multi-criteria analysis, SMCA and frequency ratio (FR) method. Then, I have evaluated the results which will support preliminary landslide risk level identification at the local level. Existing secondary data and landslide inventory extracted using satellite imageries were major data sources. Landslides in Nuwakot are concentrated within the range of 1000-1500-meter elevation of 15-25-degree convex slope with gneisses/schists formation. A result using SCMA methodology shows 47% area of Nuwakot under landslide susceptibility, of which 13.6% is highly susceptible whereas FR method resulted 27% area under high susceptible zone. The variation in susceptibility level and area between SCMA and FR methods can be attributed to differential calculated weight factor to geological factors, such as fault, lineament, and lithology. This study concludes that irrespective of methods adopted, landslide susceptibility maps and output data provide useful tools for landslide hazard risk identification and management. The necessity of robust and commonly applicable guidelines at different geographic scales is also obvious.

A review of current practices on lead ions removal from different aqueous streams

Toxic heavy metals like Lead are destructive to humans and the environment when existing above their threshold limits. Several conventional lead abatement methods are used in wastewater treatment plants to restore the ecology, food supply, and human and animal health. Many tactics are used to remove harmful Pb metals, like ion exchange, chemical precipitation, membrane filtration, and coagulation. These have a few principal approaches for removing metal ions from used water. Rapid developments in tailor-made materials science have proved to remove Lead metal using ion exchange resins, zeolite, polymeric membranes, and ionic liquids due to their low cost, surface accessibility, and unique benefits. This review paper has studied the detailed benefits and shortcomings of removing lead ions from wastewater using numerous materials, processes of production, possibly destructive properties on public health, and potential hybrid routes. In addition, this work observes the present advancements and developments in lead mitigation tools using different techniques for the past five years. Furthermore, this research review opens up to study of other materials' diverse applications in removal processes.