Micro (nano)plastics (MNPs) are pollutants of worldwide concern for their ubiquitous environmental presence and associated impacts. The higher consumption of MNPs contaminated commercial food can cause potential adverse human health effects. This review highlights the evidence of MNPs in commercial food items and summarizes different sampling, extraction, and digestion techniques for the isolation of MNPs, such as oxidizing digestion, enzymatic digestion, alkaline digestion and acidic digestion. Various methods for the characterization and quantification of microplastics (MPs) are also compared, including μ-Raman spectroscopy, μ-Fourier transform infrared spectroscopy (FTIR), thermal analysis and Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX). Finally, we share our concerns about the risks of MNPs to human health through the consumption of commercial seafood. The knowledge of the potential human health impacts at a subcellular or molecular level of consuming mariculture products contaminated with MNPs is still limited. Moreover, MNPs are somewhat limited, hard to measure, and still contentious. Due to the nutritional significance of fish consumption, the risk of exposure to MNPs and the associated health effects are of the utmost importance.
The mutating SARS-CoV-2 necessitates gauging the role of airborne particulate matter in the COVID-19 outbreak for designing area-specific regulation modalities based on the environmental state-of-affair. To scheme the protocols, the hotspots of air pollutants such as PM2.5, PM10, NH3, NO, NO2, SO2, and and environmental factors including relative humidity (RH), and temperature, along with COVID-19 cases and mortality from January 2020 till December 2020 from 29 different ground monitoring stations spanning Delhi, are mapped. Spearman correlation coefficients show a positive relationship between SARS-COV-2 with particulate matter (PM2.5 with r > 0.36 and PM10 with r > 0.31 and p-value <0·001). Besides, SARS-COV-2 transmission showed a substantial correlation with NH3 (r = 0.41), NO2 (r = 0.36), and NO (r = 0.35) with a p-value <0.001, which is highly indicative of their role in SARS-CoV-2 transmission. These outcomes are associated with the source of PM and its constituent trace elements to understand their overtone with COVID-19. This strongly validates temporal and spatial variation in COVID-19 dependence on air pollutants as well as on environmental factors. Besides, the bottlenecks of missing latent data, monotonous dependence of variables, and the role air pollutants with secondary environmental variables are discussed. The analysis set the foundation for strategizing regional-based modalities considering environmental variables (i.e., pollutant concentration, relative humidity, temperature) as well as urban and transportation planning for efficient control and handling of future public health emergencies.
Gestagens are common pollutants accumulated in the aquatic ecosystem. Gestagens are comprised of natural gestagens (i.e. progesterone) and synthetic gestagens (i.e. progestins). The major contributors of gestagens in the environment are paper plant mill effluent, wastewater treatment plants, discharge from pharmaceutical manufacturing, and livestock farming. Gestagens present in the aquatic environment interact with progesterone receptors and other steroid hormone receptors, negatively influencing fish reproduction, development, and behavior. In fish, the gonadotropin induces 17α, 20β-dihydroxy-4-pregnen-3-one (DHP) production, an important steroid hormone involved in gametogenesis. DHP interacts with the membrane progestin receptor (mPR), which regulates sperm motility and oocyte maturation. Gestagens also interfere with the hypothalamic-pituitary-gonadal (HPG) axis, which results in altered hormone levels in fish. Moreover, recent studies showed that even at low concentrations exposure to gestagens can have detrimental effects on fish reproduction, including reduced egg production, masculinization, feminization in males, and altered sex ratio, raising concerns about their impact on the fish population. This review highlights the hormonal regulation of sperm motility, oocyte maturation, the concentration of environmental gestagens in the aquatic environment, and their detrimental effects on fish reproduction. However, the long-term and combined impacts of multiple gestagens, including their interactions with other pollutants on fish populations and ecosystems are not well understood. The lack of standardized regulations and monitoring protocols for gestagens pollution in wastewater effluent hampers effective control and management. Nonetheless, advancements in analytical techniques and biomonitoring methods provide potential solutions by enabling better detection and quantification of gestagens in aquatic ecosystems.
Semiconductor metal oxide with TiO2 nanoparticles removes hazardous compounds from environmental samples. TiO2 nanoparticles have shown potential as an efficient photocatalyst by being employed as a nano-catalyst for the breakdown of organic contaminants in wastewater samples. To separate substances from contaminated samples, combined UV and visible light irradiation has been used. Sol-gel synthesis was used to produce a copper chromite-titanium nanocomposite, which was then evaluated using analytical methods, such as XRD, BET, DRS-UV, and FT-IR. Using visible light, the photocatalytic activity of a nanocomposite made of CuCr2O4 and TiO2 was investigated for its role in the breakdown of malachite green. The effects of several parameters, including pH change, anions presence, contact time, catalyst amount, concentration variation, and the kinetics of photocatalytic degradation were investigated. The magnitude of transition energy calculated using UV-DRS spectra was found to be 3.1 eV for CuCr2O4-TiO2 nanocomposite. Maximum degradation was observed at pH 7.0. The surface area and pore volume of the co-doped samples of Cr2O4 - TiO2 obtained from BET were found to be 6.1213 m2/g and 0.045063 cm3/g respectively. The average particle size of the catalyst of the nano-catalysts calculated from XRD was found to be 8 nm for TiO2 and 66 nm for TiO2-CuCrO4. The peaks obtained in FTIR between the range of 900-500 cm-1 were due to the presence of an aromatic compound. The binding mechanism of a dye molecule to the surface of CuCr2O4-TiO2 nanocomposite was analysed using quantum chemical calculations with the self-consistent reaction field technique employing integral equation formalism for the polarized continuum method and the UFF atomic radii set.
Microbial degradation of pesticide residues has the potential to reduce their hazards to human and environmental health. However, in some cases, degradation can activate pesticides, making them more toxic to microbes. Here we report on the β-cypermethrin (β-CY) toxicity to Bacillus cereus GW-01, a recently described β-CY degrader, and effects of antioxidants on β-CY degradation. GW-01 exposed to β-CY negatively affected the growth rate. The highest maximum specific growth rate (μm) appeared at 25 mg/L β-CY. β-CY induced the oxidative stress in GW-01. The activities of superoxide dismutase (SOD), catalyse (CAT), and glutathione-S-transferase (GST) were significantly higher than that in control (p
The present study highlights the treatment of industrial effluent, which is one of the most life-threatening factors. Herein, for the first time, two types of NiO (green and black) photocatalysts were prepared by facile chemical precipitation and thermal decomposition methods separately. The synthesized NiO materials were demonstrated with various instrumental techniques for finding their characteristics. The X-ray diffraction studies (XRD) and X-ray photoelectron spectroscopy (XPS) revealed the presence of Ni2O3 in black NiO material. The transmission electron microscopic (TEM) images engrained the nanospherical shaped green NiO and nanoflower shaped black NiO/Ni2O3 materials. Further, the band gap of black NiO nanoflower was 2.9 eV compared to green NiO having 3.8 eV obtained from UV-vis spectroscopy. Meanwhile, both NiO catalysts were employed for visible light degradation, which yields a 60.3% efficiency of black NiO comparable to a 4.3% efficiency of green NiO within 180 min of exposure. The higher degrading efficiency of black NiO was due to the presence of Ni2O3 and the development of pores, which was evident from the Barrett-Joyner-Halenda (BJH) method. Type IV hysteresis was observed in black NiO nanoflowers with high surface area and pore size measurements. This black NiO/Ni2O3 synthesized from the thermal decomposition method has promoted better photocatalytic degradation of 4-chlorophenol upon exposure to visible light and is applicable for other industrial pollutants.
Atopic dermatitis is one of the most widespread chronic inflammatory skin conditions that can occur at any age, though the prevalence is highest in children. The purpose of the current study was to prepare and optimize the azelaic acid (AzA) loaded SNEDDS using Pseudo ternary phase diagram, which was subsequently incorporated into the Carbopol 940 hydrogel for the treatment of atopic dermatitis. The composition was evaluated for size, entrapment efficiency, in vitro, ex vivo, and in vivo studies. The polydispersity index of the optimized preparation was found to be less than 0.5, and the size of the distributed globules was found to be 151.20 ± 3.67 nm. The SNEDDS hydrogel was characterized for pH, viscosity, spreadability, and texture analysis. When compared to the marketed formulation, SNEDDS hydrogel was found to have a higher rate of permeation through the rat skin. In addition, a skin irritation test carried out on experimental animals showed that the SNEDDS formulation did not exhibit any erythematous symptoms after a 24-h exposure. In conclusion, the topical delivery of AzA through the skin using SNEDDS hydrogel could prove to be an effective approach for the treatment of atopic dermatitis.
Carbohydrates are a class of macromolecules that has significant potential across several domains, including the organisation of genetic material, provision of structural support, and facilitation of defence mechanisms against invasion. Their molecular diversity enables a vast array of essential functions, such as energy storage, immunological signalling, and the modification of food texture and consistency. Due to their rheological characteristics, solubility, sweetness, hygroscopicity, ability to prevent crystallization, flavour encapsulation, and coating capabilities, carbohydrates are useful in food products. Carbohydrates hold potential for the future of therapeutic development due to their important role in sustained drug release, drug targeting, immune antigens, and adjuvants. Bio-based packaging provides an emerging phase of materials that offer biodegradability and biocompatibility, serving as a substitute for traditional non-biodegradable polymers used as coatings on paper. Blending polyhydroxyalkanoates (PHA) with carbohydrate biopolymers, such as starch, cellulose, polylactic acid, etc., reduces the undesirable qualities of PHA, such as crystallinity and brittleness, and enhances the PHA's properties in addition to minimizing manufacturing costs. Carbohydrate-based biopolymeric nanoparticles are a viable and cost-effective way to boost agricultural yields, which is crucial for the increasing global population. The use of biopolymeric nanoparticles derived from carbohydrates is a potential and economically viable approach to enhance the quality and quantity of agricultural harvests, which is of utmost importance given the developing global population. The carbohydrate biopolymers may play in plant protection against pathogenic fungi by inhibiting spore germination and mycelial growth, may act as effective elicitors inducing the plant immune system to cope with pathogens. Furthermore, they can be utilised as carriers in controlled-release formulations of agrochemicals or other active ingredients, offering an alternative approach to conventional fungicides. It is expected that this review provides an extensive summary of the application of carbohydrates in the realms of food, pharmaceuticals, and environment.
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.
Bio-coating, a recent and promising approach in attached microalgal cultivation systems, has garnered attention due to its efficiency in enhancing immobilized algal growth, particularly in submerged cultivation systems. However, when the cells are cultured on thin solid microporous substrates that physically separate them from the nutrient medium, it remains unclear whether the applied bio-coatings still have a significant impact on algal growth or the subsequent rates of algal organic matter (AOM) release. Therefore, this current work investigated the role of bio-coatings on the microalgal monoculture growth of one freshwater species, Chlorella vulgaris ESP 31, and one marine species, Cylindrotheca fusiformis on a hydrophilic substrate, polyvinylidene fluoride membrane in a permeated cultivation system. Wide range of bio-coating sources were adapted, with the result demonstrating that bacteria-derived coating promoted algal growth by as high as 140% when compared with the control group for both species. Interestingly, two distinct adaptation mechanisms were observed between the species, with only C. fusiformis demonstrating a positive correlation between cell growth and AOM productivity, particularly in its extracellularly bound fractions. It is worth noting that despite this specific fraction exhibiting the lowest content among all; it displayed significant relevance in terms of AOM productivity. High extracellular protein-to-polysaccharide ratio (>5.7 fold) quantified on bacterial intracellular exudate-coated membranes indirectly revealed an underlying symbiotic microalgal-bacterial interaction. This is the first study showing how bio-coating influenced AOM yield without any physical interaction between microalgae and bacteria. It further confirms the practical benefits of bio-coating in attached cultivation systems.
Coastal ecosystems are facing heightened risks due to human-induced climate change, including rising water levels and intensified storm events. Accurate bathymetry data is crucial for assessing the impacts of these threats. Traditional data collection methods can be cost-prohibitive. This study investigates the feasibility of using freely accessible Landsat and Sentinel satellite imagery to estimate bathymetry and its correlation with hydrographic chart soundings in Port Klang, Malaysia. Through analysis of the blue and green spectral bands from the Landsat 8 and Sentinel 2 datasets, a bathymetry map of Port Klang's seabed is generated. The precision of this derived bathymetry is evaluated using statistical metrics like Root Mean Square Error (RMSE) and the coefficient of determination. The results reveal a strong statistical connection (R2 = 0.9411) and correlation (R2 = 0.7958) between bathymetry data derived from hydrographic chart soundings and satellite imagery. This research not only advances our understanding of employing Landsat imagery for bathymetry assessment but also underscores the significance of such assessments in the context of climate change's impact on coastal ecosystems. The primary goal of this research is to contribute to the comprehension of Landsat imagery's utility in bathymetry evaluation, with the potential to enhance safety protocols in seaport terminals and provide valuable insights for decision-making concerning the management of coastal ecosystems amidst climate-related challenges. The findings of this research have practical implications for a wide range of stakeholders involved in coastal management, environmental protection, climate adaptation and disaster preparedness.
Perfluoroalkyl carboxylic acids (PFCAs) are sub-class of perfluoroalkyl substances commonly detected in water matrices. They are persistent in the environment, hence highly toxic to living organisms. Their occurrence at trace amount, complex nature and prone to matrix interference make their extraction and detection a challenge. This study consolidates current advancements in solid-phase extraction (SPE) techniques for the trace-level analysis of PFCAs from water matrices. The advantages of the methods in terms of ease of applications, low-cost, robustness, low solvents consumption, high pre-concentration factors, better extraction efficiency, good selectivity and recovery of the analytes have been emphasized. The article also demonstrated effectiveness of some porous materials for the adsorptive removal of the PFCAs from the water matrices. Mechanisms of the SPE/adsorption techniques have been discussed. The success and limitations of the processes have been elucidated.
Polycyclic aromatic hydrocharbons (PAHs) are a class of highly toxic pollutants that are highly detrimental to the ecosystem. Landfill leechate emanated from municipal solid waste are reported to constitute significant PAHs. In the present investigation, three Fenton proceses, namely conventional Fenton, photo-fenton and electro-fenton methods have been employed to treat landfill leehcate for removing PAHs from a waste dumpig yard. Response surface methodology (RSM) and artificial neural network (ANN) methodologies were adopted to optimize and validate the conditions for optimum oxidative removal of COD and PAHs. The statistical analysis results showed that all independent variables chosen in the study are reported to have significant influence of the removal effects with P-values <0.05. Sensitivity analysis by the developed ANN model showed that the pH had the highest significance of 1.89 in PAH removal when compared to the other parameters. However for COD removal, H2O2 had the highest relative importance of 1.15, followed by Fe2+ and pH. Under optimal treatment conditions, the photo-fenton and electro-fenton processes showed better removal of COD and PAH compared to the Fenton process. The photo-fenton and electro-fenton treatment processes removed 85.32% and 74.64% of COD and 93.25% and 81.65% of PAHs, respectively. Also the investigations revelaed the presence of 16 distinct PAH compunds and the removal percentage of each of these PAHs are also reported. The PAH treatment research studies are generally limited to the assay of removal of PAH and COD levels. In the present investigation, in addition to the treatment of landfill leachate, particle size distribution analysis and elemental characterization of the resultant iron sludge by FESEM and EDX are reported. It was revealed that elemental oxygen is present in highest percentage, followed by iron, sulphur, sodium, chlorine, carbon and potassium. However, iron percentage can be reduced by treating the Fenton-treated sample with NaOH.
Airborne Microplastics (MPs), an emerging environmental issue, have gained recent attention due to their newfound presence in indoor environments. Utilizing the Web of Science database for literature collection, the paper presents a comprehensive review of airborne MPs including emission sources, assessment methods, exposure risks, and mitigation strategies. This review delves into the diverse sources and mechanisms influencing indoor airborne MP pollution, underscoring the complex interplay between human activities, ventilation systems, and the characteristics of indoor environments. Major sources include the abrasion of synthetic textiles and the deterioration of flooring materials, with factors like carpeting, airflow, and ventilation significantly impacting MP levels. Human activities, such as increased movement in indoor spaces and the intensive use of plastic-based personal protective equipment (PPE) post-pandemic, notably elevate indoor MP concentrations. The potential health impacts of airborne MPs are increasingly concerning, with evidence suggesting their role in respiratory, immune, and nervous system diseases. Despite this, there is a scarcity of information on MPs in diverse indoor environments and the inhalation risks associated with the frequent use of PPE. This review also stresses the importance of developing effective strategies to reduce MP emissions, such as employing HEPA-filtered vacuums, minimizing the use of synthetic textiles, and enhancing indoor ventilation. Several future research directions were proposed, including detailed temporal analyses of indoor MP levels, interactions of MP with other atmospheric pollutants, the transport dynamics of inhalable MPs (≤10 μm), and comprehensive human exposure risk assessments.
Carbon capture technologies are becoming increasingly crucial in addressing global climate change issues by lowering CO2 emissions from industrial and power generation activities. Post-combustion carbon capture, which uses membranes instead of adsorbents, has emerged as one of promising and environmentally friendly approaches among these technologies. The operation of membrane technology is based on the premise of selectively separating CO2 from flue gas emissions. This provides a number of different benefits, including improved energy efficiency and decreased costs of operation. Because of its adaptability to changing conditions and its low impact on the surrounding ecosystem, it is an appealing choice for a diverse array of uses. However, there are still issues to be resolved, such as those pertaining to establishing a high selectivity, membrane degradation, and the costs of the necessary materials. In this article, we evaluate and explore the prospective applications and roles of membrane technologies to control climate change by post-combustion carbon capturing. The primary proposition suggests that the utilization of membrane-based carbon capture has the potential to make a substantial impact in mitigating CO2 emissions originating from industrial and power production activities. This is due to its heightened ability to selectively absorb carbon, better efficiency in energy consumption, and its flexibility to various applications. The forthcoming challenges and potential associated with the application of membranes in post-carbon capture are also discussed.
Enhancing crop yield to accommodate the ever-increasing world population has become critical, and diminishing arable land has pressured current agricultural practices. Intensive farming methods have been using more pesticides and insecticides (biocides), culminating in soil deposition, negatively impacting the microbiome. Hence, a deeper understanding of the interaction and impact of pesticides and insecticides on microbial communities is required for the scientific community. This review highlights the recent findings concerning the possible impacts of biocides on various soil microorganisms and their diversity. This review's bibliometric analysis emphasised the recent developments' statistics based on the Scopus document search. Pesticides and insecticides are reported to degrade microbes' structure, cellular processes, and distinct biochemical reactions at cellular and biochemical levels. Several biocides disrupt the relationship between plants and their microbial symbionts, hindering beneficial biological activities that are widely discussed. Most microbial target sites of or receptors are biomolecules, and biocides bind with the receptor through a ligand-based mechanism. The biomarker action mechanism in response to biocides relies on activating the receptor site by specific biochemical interactions. The production of electrophilic or nucleophilic species, free radicals, and redox-reactive agents are the significant factors of biocide's metabolic reaction. Most studies considered for the review reported the negative impact of biocides on the soil microbial community; hence, technological development is required regarding eco-friendly pesticide and insecticide, which has less or no impact on the soil microbial community.
The study investigates the potential of utilizing banana trunk-derived porous activated biochar enriched with SO3H- as a catalyst for eco-friendly biodiesel production from the microalga Chlorella vulgaris. An extensive analysis, employing advanced techniques such as XRD, FTIR, TGA, XPS, NH3-TPD, BET, SEM-EDX, and TEM, was conducted to elucidate the physicochemical properties of BT-SO3H catalysts. The synthesized catalyst demonstrated its efficiency in converting the total lipids of Chlorella vulgaris into biodiesel, with varying concentrations of 3%, 5%, and 7%. Notably, using a 5% BT-SO3H concentration resulted in remarkably higher biodiesel production about 58.29%. Additionally, the fatty acid profile of C. vulgaris biodiesel indicated that C16:0 was the predominant fatty acid at 24.31%, followed by C18:1 (19.68%), C18:3 (11.45%), and C16:1 (7.56%). Furthermore, the biodiesel produced via 5% BT-SO3H was estimated to have higher levels of saturated fatty acids (SFAs) at 34.28%, monounsaturated fatty acids (MUFAs) at 30.70%, and polyunsaturated fatty acids (PUFAs) at 24.24%. These findings highlight the promising potential of BT-SO3H catalysts for efficient and environmentally friendly biodiesel production from microalgal species.
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.
Bangladesh is currently experiencing significant infrastructural development in road networking system through the construction or reconstruction of multiple roads and highways. Consequently, there is a rise in traffic intensity on roads and highways, along with a significant contamination of adjacent agricultural soils with heavy metals. The purpose of this study was to evaluate the ecological risk, health risk and the abundance of seven heavy metals (Cu, Mn, Pb, Cd, Cr, As, and Ni) in three distance gradients (0, 300, and 500 m) of agricultural soil along the Dhaka-Chattogram highway. The concentration of heavy metals was measured with an Atomic Absorption Spectrophotometer (AAS) on a total of 36 soil samples that were taken from 12 different sampling sites. Based on the findings, Cd had a high contamination factor for all distance gradients, whereas Cr had a moderate contamination factor in 67% of the study areas. According to the Pollution Load Index (PLI), Cd, Cr, and Pb were the predominant pollutants. Principal component analysis (PCA) result shows these metals mainly came from anthropogenic sources. The considerable positive correlations between Cu-Pb, Cu-Cd, Pb-Cd, and Cr-Ni all pointed to shared anthropogenic origins. As per Potential Ecological Risk Assessment (PERI) analysis, Pb, Cd, Cr, and Ni each contribute significantly and pose a moderate threat. The Target Hazard Quotient (THQ) values for all pathways of exposure to Pb and Cr in soils were more than 1, which would pose a significant risk to human health in the following order: THQadult female > THQadult male > THQchildren. This study will help to evaluate the human health risk and develop a better understanding of the heavy metal abundance scenario in the agricultural fields adjacent to this highway.
Agriculture is a leading sector in international initiatives to mitigate climate change and promote sustainability. This article exhaustively examines the removals and emissions of greenhouse gases (GHGs) in the agriculture industry. It also investigates an extensive range of GHG sources, including rice cultivation, enteric fermentation in livestock, and synthetic fertilisers and manure management. This research reveals the complex array of obstacles that are faced in the pursuit of reducing emissions and also investigates novel approaches to tackling them. This encompasses the implementation of monitoring systems powered by artificial intelligence, which have the capacity to fundamentally transform initiatives aimed at reducing emissions. Carbon capture technologies, another area investigated in this study, exhibit potential in further reducing GHGs. Sophisticated technologies, such as precision agriculture and the integration of renewable energy sources, can concurrently mitigate emissions and augment agricultural output. Conservation agriculture and agroforestry, among other sustainable agricultural practices, have the potential to facilitate emission reduction and enhance environmental stewardship. The paper emphasises the significance of financial incentives and policy frameworks that are conducive to the adoption of sustainable technologies and practices. This exhaustive evaluation provides a strategic plan for the agriculture industry to become more environmentally conscious and sustainable. Agriculture can significantly contribute to climate change mitigation and the promotion of a sustainable future by adopting a comprehensive approach that incorporates policy changes, technological advancements, and technological innovations.