With rapid growing world population and increasing demand for natural resources, the production of sufficient food, feed for protein and fat sources and sustainable energy presents a food insecurity challenge globally. Insect biorefinery is a concept of using insect as a tool to convert biomass waste into energy and other beneficial products with concomitant remediation of the organic components. The exploitation of insects and its bioproducts have becoming more popular in recent years. This review article presents a summary of the current trend of insect-based industry and the potential organic wastes for insect bioconversion and biorefinery. Numerous biotechnological products obtained from insect biorefinery such as biofertilizer, animal feeds, edible foods, biopolymer, bioenzymes and biodiesel are discussed in the subsequent sections. Insect biorefinery serves as a promising sustainable approach for waste management while producing valuable bioproducts feasible to achieve circular bioeconomy.
Intensive studies have been performed on the improvement of bioethanol production by transformation of lignocellulose biomass. In this study, the digestibility of corn stover was dramatically improved by using laccase immobilized on Cu2+ modified recyclable magnetite nanoparticles, Fe3O4-NH2. After digestion, the laccase was efficiently separated from slurry. The degradation rate of lignin reached 40.76%, and the subsequent cellulose conversion rate 38.37% for 72 h at 35 °C with cellulase at 50 U g-1 of corn stover. Compared to those of free and inactivated mode, the immobilized laccase pre-treatment increased subsequent cellulose conversion rates by 23.98% and 23.34%, respectively. Moreover, the reusability of immobilized laccase activity remained 50% after 6 cycles. The storage and thermal stability of the fixed laccase enhanced by 70% and 24.1% compared to those of free laccase at 65 °C, pH 4.5, respectively. At pH 10.5, it exhibited 16.3% more activities than its free mode at 35 °C. Our study provides a new avenue for improving the production of bioethanol with immobilized laccase for delignification using corn stover as the starting material.
The present study aimed to assess the efficiency of silver bio-nanoparticles (Ag-NPs) in inactivating of the Aspergillus fumigatus, A. parasiticus and A. flavus var. columnaris and A. aculeatus spores. The AgNPs were synthesized in secondary metabolic products of Penicillium pedernalens 604 EAN. The inactivation process was optimized by response surface methodology (RSM) as a function of Ag NPs volume (1-10 μL/mL); time (10-120 min); pH (5-8); initial fungal concentrations (log10) (3-6). The artificial neural network (ANN) model was used to understand the behavior of spores for the factors affecting inactivation process. The best conditions to achieved SAL 10-6 of the fungal spores were recorded with 3.46 μl/mL of AgNPs, after 120 min at pH 5 and with 6 log of initial fungal spore concentrations, at which 5.99 vs. 6.09 (SAL 10-6) log reduction was recorded in actual and predicted results respectively with coefficient of 87.00%. The ANN revealed that the timehas major contribution in the inactivation process compare to Ag NPs volume. The fungal spores were totally inactivated (SAL 10-6, 6 log reduction with 99.9999%) after 110 min of the inactivation process, 10 min more was required to insure the irreversible inactivation of the fungal spores. The absence of protease and cellulase enzymes production confirm the total inactivation of the fungal spores. FESEM analysis revealed that the AgNPs which penetrated the fungal spores leading to damage and deform the fungal spore morphology. The AFM analysis confirmed the total spore surface damage. The bands in the range of the Raman spectroscopy from 1300 to 1600 cm-1 in the inactivated spores indicate the presence of CH3, CH2 and the deformation of lipids released outside the spore cytoplasm. These finding indicate that the AgNPs has high potential as a green alternative inactivation process for the airborne fungal spores.
The International Maritime Organization has set a goal to achieve a 50% reduction of total annual greenhouse gas emission related to the international shipping by 2050 compared to the 2008 baseline emissions. Malaysia government has taken an initiative to investigate the assessment (cost-effectiveness) of this International Maritime Organization's short-term measure on Malaysian-registered domestic ships although this measure is only for international merchant ship. To achieve this, this paper collected the ship's data from the shipowners from 25 sample ships. Engine power limitation is the most cost-effective option, but low power limits can lead to substantially increased sailing times. Based on cost-efficiency analysis, it creates for the purpose of compliance with the operational carbon intensity indicator. It found that even if it is possible to bring an asset back into service, it may not be possible to do so in a manner that generates a profit or complies with applicable regulations. In these situations, it may be more prudent to scrap the asset rather than run the risk of having it become a stranded asset. This is especially true for older tankers. Alternatives with lengthy payback periods are not desirable for the domestic tanker fleet that is already in operation.
Climate change and coastal ecosystems have become challenging subjects for world sustainability. Humans, animals, and other ocean habitats are primarily affected by the harmful changes in climate. Coastal ecosystems support biodiversity and a wide range of species that serve as habitats for many commercially important fish species and enhance human activities in coastal areas. By engaging in coastal outdoor activities, individuals can experience numerous physical and mental health benefits, foster environmental awareness. This study provided valuable insights into the importance of coastal outdoor activities and their potential to improve our quality of life. This study undertook a challenging subject where we graphically and econometrically analyze the relationship and linkages among coastal indicators with other climate-concerning factors. The study comprises the ordinary regression and comparative analysis among the four largest coastline countries in the world. The study took a sample from Canada, Indonesia, Norway, and the Russian Federation from 1990 to 2022. The data is selected on a convenient basis. Results declared that each country has its unique challenges and opportunities in mitigating adverse climate change and retaining a sustainable coastal ecosystem. The study surprisingly revealed that climate change insignificantly affects the coastal ecosystem in Indonesia and the Russian Federation while it inversely affects the coastal ecosystem in Canada and Norway, showed that climate change on average declines coastal production by 0.0041922 and 0.0261104 in Canada and Norway respectively. The detailed review is given in the results section; however, the pooling analysis proved that at the aggregate level, a one percent increase in climate change caused a 0.02266-tonne decline in coastal ecosystems in the four largest coastline nations. There is a need for policies tend to increase CAP activities by implementing practical marine protected areas. Furthermore, scientific research and monitoring will be beneficial in restoring coastal sustainability.
The impact of air pollution in Chennai metropolitan city, a southern Indian coastal city was examined to predict the Air Quality Index (AQI). Regular monitoring and prediction of the Air Quality Index (AQI) are critical for combating air pollution. The current study created machine learning models such as XGBoost, Random Forest, BaggingRegressor, and LGBMRegressor for the prediction of the AQI using the historical data available from 2017 to 2022. According to historical data, the AQI is highest in January, with a mean value of 104.6 g/gm, and the lowest in August, with a mean AQI value of 63.87 g/gm. Particulate matter, gaseous pollutants, and meteorological parameters were used to predict AQI, and the heat map generated showed that of all the parameters, PM2.5 has the greatest impact on AQI, with a value of 0.91. The log transformation method is used to normalize datasets and determine skewness and kurtosis. The XGBoost model demonstrated strong performance, achieving an R2 (correlation coefficient) of 0.9935, a mean absolute error (MAE) of 0.02, a mean square error (MSE) of 0.001, and a root mean square error (RMSE) of 0.04. In comparison, the LightGBM model's prediction was less effective, as it attained an R2 of 0.9748. According to the study, the AQI in Chennai has been increasing over the last two years, and if the same conditions persist, the city's air pollution will worsen in the future. Furthermore, accurate future air quality level predictions can be made using historical data and advanced machine learning algorithms.
Food loss or waste is a far-reaching problem and has indeed become a worrying issue that is growing at an alarming rate. Fruits and vegetables are lost or wasted at the highest rate among the composition of food waste. Furthermore, the world is progressing toward sustainable development; hence, an efficient approach to valorise fruit and vegetable waste (FVW) is necessary. A simple phenotypic characterisation of microbiota isolated from the fermented FVW was conducted, and its effectiveness toward wastewater treatment was investigated. Presumptive identification suggested that yeast is dominant in this study, accounting for 85% of total isolates. At the genus level, the enriched medium's microbial community consists of Saccharomyces, Bacillus and Candida. Ammonium in the wastewater can enhance certain bacteria to grow, such as lactic acid bacteria, resulting in decreased NH4+ concentration at the end of the treatment to 0.5 mg/L. In addition, the fermented biowaste could reduce PO43- by 90% after the duration of treatment. Overall, FVW is a valuable microbial resource, and the microbial population enables a reduction in organic matter such as NH4+ and PO43-. This study helps explore the function and improve the effectiveness of utilising biowaste by understanding the microorganisms responsible for producing eco-enzyme.
The Guerouaou aquifer investigation spanning 280 km2 in Ain Zohra yields promising outcomes, instilling optimism for regional water quality. These analyses were applied to 45 sampling instances from 43 wells, enabling a comprehensive water quality assessment. Groundwater conductivity ranged from medium to high, peaking at 18360 ms/cm2. The conductivity reveals insights about the groundwater's mineralization. Key physiochemical parameters fell within desirable thresholds, bolstering the positive perspective. HCO3- levels spanned 82-420 mg/L, while chloride content ranged from 38 to 5316 mg/L, benefiting water quality. NO3- ions, vital for gauging pollution, ranged from 0 to 260 mg/L, indicating favorable results. Cation concentrations exhibited encouraging variations: Ca2+- 24 to 647 mg/L, Mg2+- 12 to 440 mg/L, Na+- 18 to 2722 mg/L, K+- 1.75 to 28.65 mg/L. These collectively favor water quality. Halite breakdown dominated mineralization, as evidenced by the prevalence of Na-Cl-Na-SO4 facies. Water resource management and local communities need effective management and mitigation strategies to prevent saltwater intrusion.
This study aims to produce hydrochar from high-ash low-lipid Chlorella vulgaris biomass via hydrothermal carbonization (HTC) process. The effects of hydrothermal temperature and retention time with respect to the physicochemical properties of hydrochar were studied in the range of 180-250 °C and 0.5-4 h, respectively. It was found that the hydrothermal temperature had resulted in a significant reduction of hydrochar yield as compared to the retention time. The raw microalgal biomass was successfully converted into an energy densified hydrochar via an optimized HTC reaction, with higher heating value (HHV) of 24.51 kJ/g, which was approximately two-times higher than that of raw biomass. In addition, the overall carbon recovery rate and energy yield were in the range of 53.2-86.4% and 46.9-76.6%, respectively. The high quality of the produced hydrochar was further supported by the plot of van Krevelen diagram and combustion behaviour analysis. Besides, the aqueous phase collected from HTC process could be further used as nutrients source to cultivate C. vulgaris, in which up to 70% of the biomass yield could be attained as compared to the control cultivation condition. The reusability of the aqueous phase collected from HTC process as an alternative nutrients source to cultivate microalgal indicated the feasibility and positive integration of HTC process in microalgal biofuel processing chain.
Cancer is an intricate disease that develops as a response to a combination of hereditary and environmental risk factors, which then result in a variety of changes to the genome. The cluster of differentiation (CD44) is a type of transmembrane glycoprotein that serves as a potential biomarker for cancer stem cells (CSC) and viable targets for therapeutic intervention in the context of cancer therapy. Hyaluronic acid (HA) is a linear polysaccharide that exhibits a notable affinity for the CD44 receptor. This characteristic renders it a promising candidate for therapeutic interventions aimed at selectively targeting CD44-positive cancer cells. Treating cancer via non-viral vector-based gene delivery has changed the notion of curing illness through the incorporation of therapeutic genes into the organism. The objective of this review is to provide an overview of various hyaluronic acid-modified lipoplexes and polyplexes as potential drug delivery methods for specific forms of cancer by effectively targeting CD44.
Psoriasis is a deleterious auto-immune disorder which seriously harms the patients physical and mental health. CD44 are found to be over-expressed on psoriatic lesions which are highly responsible for epidermal hyperproliferation and inflammation. Gallic acid (GA), a phenolic acid natural compound has potential inhibitory impact on pro-inflammatory transcription factors. However, the penetration across skin and availability is low when applied topically, making the treatment extremely challenging. Considering such factors, we developed GA loaded chitosan nanoparticles and modified with hyaluronic acid (HA) (HA@CS-GA NP) to assess the therapeutic potential against psoriasis. The formulations were characterized by DSC, zetasizer and TEM for assuring the development of nanosystems. GA loaded CS NP had a particle size of 207.2 ± 0.08 nm while after coating with HA, the size increased to 220.1 ± 0.18 nm. The entrapment efficiency was 93.24 ± 0.132% and drug loading of 73.17 ± 0.23%. The in vitro cell viability assessment study confirmed enhanced anti-proliferative effect of HA@CS-GA NP over plain GA which is due to high sensitivity towards HaCaT cell. The in vivo results on imiquimod induced psoriasis model indicated that CD44 receptor mediated targeted approach of HA@CS-GA NP gel had great potential in restricting the keratinocyte hyperproliferation and circumventing psoriasis. For the therapy of further skin-related conditions, HA modified nanoparticles should be investigated extensively employing genes, antibodies, chemotherapeutics, or natural substances.
The temperature of surface and epilimnetic waters, closely related to regional air temperatures, responds quickly and directly to climatic changes. As a result, lake surface temperature (LSWT) can be considered an effective indicator of climate change. In this study, we reconstructed and investigated historical and future LSWT across different scenarios for over 80 major lakes in mainland Southeast Asia (SEA), an ecologically diverse region vulnerable to climate impacts. Five different predicting models, incorporating statistical, machine and deep learning approaches, were trained and validated using ERA5 and CHIRPS climatic feature datasets as predictors and 8-day MODIS-derived LSWT from 2000 to 2020 as reference dataset. Best performing model was then applied to predict both historical (1986-2020) and future (2020-2100) LSWT for SEA lakes, utilizing downscaled climatic CORDEX-SEA feature data and multiple Representative Concentration Pathway (RCP). The analysis uncovered historical and future thermal dynamics and long-term trends for both daytime and nighttime LSWT. Among 5 models, XGboost results the most performant (NSE 0.85, RMSE 1.14 °C, MAE 0.69 °C, MBE -0.08 °C) and it has been used for historical reconstruction and future LSWT prediction. The historical analysis revealed a warming trend in SEA lakes, with daytime LSWT increasing at a rate of +0.18 °C/decade and nighttime LSWT at +0.13 °C/decade over the past three decades. These trends appeared of smaller magnitude compared to global estimates of LSWT change rates and less pronounced than concurrent air temperature and LSWT increases in neighbouring regions. Projections under various RCP scenarios indicated continued LSWT warming. Daytime LSWT is projected to increase at varying rates per decade: +0.03 °C under RCP2.6, +0.14 °C under RCP4.5, and +0.29 °C under RCP8.5. Similarly, nighttime LSWT projections under these scenarios are: +0.03 °C, +0.10 °C, and +0.16 °C per decade, respectively. The most optimistic scenario predicted marginal increases of +0.38 °C on average, while the most pessimistic scenario indicated an average LSWT increase of +2.29 °C by end of the century. This study highlights the relevance of LSWT as a climate change indicator in major SEA's freshwater ecosystems. The integration of satellite-derived LSWT, historical and projected climate data into data-driven modelling has enabled new and a more nuanced understanding of LSWT dynamics in relation to climate throughout the entire SEA region.
CO2 sequestration into coalbed seams is one of the practical routes for mitigating CO2 emissions. The adsorption mechanisms of CO2 onto Malaysian coals, however, are not yet investigated. In this research CO2 adsorption isotherms were first performed on dry and wet Mukah-Balingian coal samples at temperatures ranging from 300 to 348 K and pressures up to 6 MPa using volumetric technique. The dry S1 coal showed the highest CO2 adsorption capacity of 1.3 mmol g-1, at 300 K and 6 MPa among the other coal samples. The experimental results of CO2 adsorption were investigated using adsorption isotherms, thermodynamics, and kinetic models. Nonlinear analysis has been employed to investigate the data of CO2 adsorption onto coal samples via three parameter isotherm equilibrium models, namely Redlich Peterson, Koble Corrigan, Toth, Sips, and Hill, and four parameter equilibrium model, namely Jensen Seaton. The results of adsorption isotherm suggested that the Jensen Seaton model described the experimental data well. Gibb's free energy change values are negative, suggesting that CO2 adsorption onto the coal occurred randomly. Enthalpy change values in the negative range established that CO2 adsorption onto coal is an exothermic mechanism. Webber's pore-diffusion model, in particular, demonstrated that pore-diffusion was the main controlling stage in CO2 adsorption onto coal matrix. The activation energy of the coals was calculated to be below -13 kJ mol-1, indicating that adsorption of CO2 onto coals occurred through physisorption. The results demonstrate that CO2 adsorption onto coal matrix is favorable, spontaneous, and the adsorbed CO2 molecules accumulate more onto coal matrix. The observations of this investigation have significant implications for a more accurate measurement of CO2 injection into Malaysian coalbed seams.
Metal-organic framework (MOF)--based composites have received significant attention in a variety of applications, including pollutant adsorption processes. The current investigation was designed to model, forecast, and optimize heavy metal (Cu2+) removal from wastewater using a MOF nanocomposite. This work has been modeled by response surface methodology (RSM) and artificial neural network (ANN) algorithms. In addition, the optimization of the mentioned factors has been performed through the RSM method to find the optimal conditions. The findings show that RSM and ANN can accurately forecast the adsorption process's the Cu2+ removal efficiency (RE). The maximum values of RE are achieved at the highest value of time (150 min), the highest value of adsorbent dosage (0.008 g), and the highest value of pH (=6). The R2 values obtained were 0.9995, 0.9992, and 0.9996 for ANN modeling of adsorption capacity based on different adsorbent dosages, Cu2+ solution pHs, and different ion concentrations, respectively. The ANN demonstrated a high level of accuracy in predicting the local minima of the graph. In addition, the RSM optimization results showed that the optimum mode for RE occurred at an adsorbent dosage value of 0.007 g and a time value of 144.229 min.
Road transport contributes over 70% of air pollution in urban areas and is the second largest contributor to the total carbon dioxide emissions in Malaysia at 21% in 2016. Transport-related air pollutants (TRAPs) such as NOx, SO2, CO and particulate matter (PM) pose significant threats to the urban population's health. Malaysia has targeted to deploy 885,000 EV cars on the road by 2030 in the Low Carbon Mobility Blueprint (LCMB). This study aims to quantify the health co-benefits of electric vehicle adoption from their impacts on air quality in Malaysia. Two EV uptake projections, i.e. LCMB and Revised EV Adoption (REVA) projections, and five electricity generation mix scenarios were modelled up to 2040. We used comparative health risk assessment to estimate the potential changes in mortality and burden of diseases (BoD) from the emissions in each scenario. Intake fractions and exposure-risk functions were used to calculate the burden from respiratory diseases (PM2.5, NOx, SO2, CO), cardiovascular diseases and lung cancer (PM2.5). Results showed that along with a net reduction of carbon emissions across all scenarios, there could be reduced respiratory mortality from NOx by 10,200 mortality (176,200 DALYs) and SO2 by 2600 mortality (45,400 DALYs) per year in 2040. However, there could also be additional 719 mortality (9900 DALYs) per year from PM2.5 and 329 mortality (5600 DALYs) from CO per year. The scale of reduction in mortality and BoD from NOx and SO2 are significantly larger than the scale of increase from PM2.5 and CO, indicating potential net positive health impacts from the EV adoption in the scenarios. The health cost savings from the reduced BoD of respiratory mortality could reach up to RM 7.5 billion per year in 2040. In conclusion, EV is a way forward in promoting a healthy and sustainable future transport in Malaysia.
This review emphasizes the role of toxic metal remediation approaches due to their broad sustainability and applicability. The rapid developmental processes can incorporate a large quantity of hazardous and unseen heavy metals in all the segments of the environment, including soil, water, air and plants. The released hazardous heavy metals (HHMs) entered into the food chain and biomagnified into living beings via food and vegetable consumption and originate potentially health-threatening effects. The physical and chemical remediation approaches are restricted and localized and, mainly applied to wastewater and soils and not the plant. The nanotechnological, biotechnological and genetical approaches required to more rectification and sustainability. A cellular, molecular and nano-level understanding of the pathways and reactions are responsible for potentially toxic metals (TMs) accumulation. These approaches can enable the development of crop varieties with highly reduced concentrations of TMs in their consumable foods and vegetables. As a critical analysis by authors observed that nanoparticles could provide very high adaptability for both in-situ and ex-situ remediation of hazardous heavy metals (HHMs) in the environment. These methods could be used for the improvement of the inbuilt genetic potential and phytoremediation ability of plants by developing transgenic. These biological processes involve the transfer of gene of interest, which plays a role in hazardous metal uptake, transport, stabilization, inactivation and accumulation to increased host tolerance. This review identified that use of nanoremediation and combined biotechnological and, transgenic could help to enhance phytoremediation efficiency in a sustainable way.
In this study, nickel-loaded perovskite oxides catalysts were synthesized via the impregnation of 10%Ni on XTiO3 (X = Ce, Sr, La, Ba, Ca, and Fe) supports and employed in the catalytic steam gasification of swine manure to produce H2-rich syngas for the first time. The synthesized catalysts were characterized using BET, H2-TPR, XRD, HR-TEM, and EDX analysis. Briefly, using perovskite supports resulted in the production of ultrafine catalyst nanoparticles with a uniform dispersion of Ni particles. According to the catalytic activity test, the gas yield showed the increment as 10% Ni/LaTiO3 < 10% Ni/FeTiO3 < 10% Ni/CeTiO3 < 10% Ni/BaTiO3 < 10% Ni/SrTiO3 < 10% Ni/CaTiO3. Meanwhile, zero coke formation was achieved due to the oxygen mobility of prepared catalysts. Also, the increase in the H2 production for the applied catalysts was in the sequence as 10% Ni/CeTiO3 < 10% Ni/FeTiO3 < 10% Ni/LaTiO3 < 10% Ni/BaTiO3 < 10% Ni/SrTiO3 < 10% Ni/CaTiO3. The maximum H2 selectivity (∼48 vol%) obtained by10% Ni/CaTiO3 was probably due to the synergistic effect of Ni and Ti on enhancing the water-gas shift reaction, and Ca on creating the maximum oxygen mobility compared to other alkaline earth metals doped at the A place of perovskite. Overall, this study provides a suitable solution for enhanced H2 production through steam gasification of swine manure along with suggesting the appropriate supports to prevent Ni deactivation by lowering coke formation at the same time.
This study was focused on identifying the region suitable for agriculture-based, using new irrigation groundwater quality plot and its spatio-temporal variation with fuzzy logic technique in a geographic information system (GIS) platform. Six hundred and eighty groundwater samples were collected during pre, southwest, northeast, and post monsoon periods. A new ternary plot was also attempted to determine the irrigation suitability of water by considering four essential parameters such as sodium adsorption ratio (SAR), permeability index (PI), Sodium percentage (Na %), and electrical conductivity (EC). The derived ternary plot was the most beneficial over other available plots, as it incorporated four parameters, and it differs from the US Salinity Laboratory (USSL) plot, such that the groundwater with higher EC could also be used for irrigation purposes, depending on the Na%. The ternary plot revealed that the groundwater predominantly manifested good to moderate category during post, northeast, and southwest monsoons. The assessment with the amount of fertilizer used during the study period showed that the NPK fertilizers were effectively used for irrigation during monsoon periods. Spatial maps on EC, Kelly's ratio, Mg hazard, Na%, PI, potential salinity (PS), SAR, residual sodium carbonate (RSC), and soluble sodium percentage (SSP) were prepared for each season using fuzzy membership values, integrated for each season. A final suitability map derived by an overlay of all the seasonal outputs has identified that the groundwater in the western and the eastern part of the study area are suitable for agriculture. The study recommends cultivation of groundwater-dependent short-term crops, along the western and northern regions of the study area during the pre-monsoon season.
The synthesis of polymer-encapsulated metal nanoparticles is a growing field of area due to their long-term uses in the development of new technologies. The present study describes the synthesis of chitosan/silver nanocomposite using kaempferol for anticancer and bactericidal activity. The formation of Kf-CS/Ag nanocomposite was confirmed by the development of a brown color and UV-absorbance around 438 nm. The IR study was utilized to determine the existence of Kf and CS in the synthesized nanocomposite. TEM analysis demonstrated that the synthesized nanocomposite have a predominantly uniform spherical shape and size ranges 7-10 nm. EDX spectrum showed the existence of Ag, C, and N elements in the nanocomposite material. Further, Kf-CS/Ag nanocomposite exhibited potential in vitro inhibitory property against triple-negative breast cancer (TNBC) cells and their IC50 values was found to be 53 μg/mL. Moreover, fluorescent assays such as DAPI and AO/EtBr confirmed the apoptosis induction ability of Kf-CS/Ag nanocomposite in MDA-MB-231 cells. The synthesized Kf-CS/Ag nanocomposite showed significant and dose-depended antibacterial property against S. aureus and P. aeruginosa. Thus, the obtained findings demonstrated that the synthesized nanocomposite can be potentially used to improve human health as biocidal nanocomposite in biomedical sectors.
The emerging growth of the electronic devices applications has arisen the serious problems of electromagnetic (EM) wave pollution which resulting in equipment malfunction. Therefore, polymer-based composites have been considered good candidates for better EMI shielding due to their significant characteristics including, higher flexibility, ultrathin, lightweight, superior conductivity, easy fabrication processing, environmentally friendly, corrosion resistive, better adhesion with physical, chemical and thermal stability. This review article focused on the concept of the EMI shielding mechanism and challenges with the fabrication of polymer-based composites. Subsequently, recent advancements in the polymer composites applications have been critically reviewed. In addition, the impact of polymers and polymer nanocomposites with different fillers such as organic, inorganic, 2D, 3D, mixture and hybrid nano-fillers on EMI shielding effectiveness has been explored. Lastly, future research directions have been proposed to overcome the limitations of current technologies for further advancement in EMI shielding materials for industrial applications. Based on reported literature, it has been found that the low thickness based lightweight polymer is considered as a best material for excellent material for next-generation electronic devices. Optimization of polymer composites during the fabrication is required for better EMI shielding. New nano-fillers such as functionalization and composite polymers are best to enhance the EMI shielding and conductive properties.