Global production of plastics has increased dramatically in recent decades and is considered a major threat to marine life and human health due to their stability, persistence, and potential to move through food chains. The study was conducted to detect, identify and quantify microplastics (MP) in the gastrointestinal tract (GI) of some commercial fish species in the North Persian Gulf in Bushehr Province: Psettodes erumei, Sphyraena jello, Sillago sihama, Metapenaeus affinis and Portunus segnis. A total of 216 plastic particles were collected from 102 individuals (72.68% of all sampled individuals; MP prevalence of 85.1% for M. affinis, 80% for P. segnis, 70% for P.erumei, 60.3% for S.sihama, 45.2% for S.jello). The average number of microplastics per organism was 2.26 ± 0.38 MP/ind (considering only species that ingested plastic, n = 102) and 1.51 ± 0.40 pieces/ind (considering all species studied, n = 140). Microfibers accounted for 58.49% of the total microplastics, followed by fragments (33.02%) and pellets (8.49%). The most common color of microplastic was black (52.83%), followed by blue (22.64%) and transparent (15.09%). The length of microplastic ranged from 100 to 5000 μm with an average of 854 ± 312 μm. Microplastics were significantly (p
To realize sound disposal of hyperaccumulator harvested from phytoremediation, hydrothermal carbonization (HTC) has been employed to obtain superior hydrochar adsorbents for removal of phosphate and ammonium from water body. A series of hydrochars have been prepared under tuned HTC conditions to tailor hydrochar with desired properties. Generally, increased temperature and prolonged reaction time facilitated acidic oxygen functional groups on hydrochars, thereby improving adsorption capacity of hydrochar. In single solute system, a superior hydrochar, derived from HTC under 260 °C for 2 h, achieved a maximum phosphate and ammonium adsorption capacity of 52.46 mg/g and 27.56 mg/g at 45 °C, respectively. In binary system, synergistic adsorption was observed only in lower solute concentration, whereas competitive adsorption occurred under higher solute concentration. Characterization and adsorption kinetics suggested chemisorption may dominate the adsorption process, thus the adsorption capacity could be improved by tuning pHpzc of hydrochar. This study firstly demonstrates the sustainable utilization of hyperaccumulators into nutrients-enriched hydrochar as fertilizer for in-situ phytoremediation of contaminated sites with minimized environmental risks towards circular economy.
Microplastics (MPs) have become a prevalent environmental concern, exerting detrimental effects on marine and terrestrial ecosystems, as well as human health. Addressing this urgent issue necessitates the implementation of coordinated waste management policies and strategies. In this study, we present a comprehensive review focusing on key results and the underlying mechanisms associated with microplastics. We examine their sources and pathways, elucidate their ecological and human health impacts, and evaluate the current state of waste management policies. By drawing upon recent research and pertinent case studies, we propose a range of practical solutions, encompassing enhanced recycling and waste reduction measures, product redesign, and innovative technological interventions. Moreover, we emphasize the imperative for collaboration and cooperation across sectors and jurisdictions to effectively tackle this pressing environmental challenge. The findings of this study contribute to the broader understanding of microplastics and provide valuable insights for policymakers, researchers, and stakeholders alike.
Antibiotic-containing wastewater is a typical biochemical refractory organic wastewater and general treatment methods cannot effectively and quickly degrade the antibiotic molecules. In this study, a novel boron-doped diamond (BDD) pulse electrochemical oxidation (PEO) technology was proposed for the efficient removal of levofloxacin (LFXN) from wastewater. The effects of current density (j), initial pH (pH0), frequency (f), electrolyte types and initial concentration (c0(LFXN)) on the degradation of LFXN were systematically investigated. The degradation kinetics under four different processes have also been studied. The possible degradation mechanism of LFXN was proposed by Density functional theory calculation and analysis of degradation intermediates. The results showed that under the optimal parameters, the COD removal efficiency (η(COD)) was 94.4% and the energy consumption (EEC) was 81.43 kWh·m-3 at t = 120 min. The degradation of LFXN at pH = 2.8/c(H2O2) followed pseudo-first-order kinetics. The apparent rate constant was 1.33 × 10-2 min-1, which was much higher than other processes. The degradation rate of LFXN was as follows: pH = 2.8/c(H2O2) > pH = 2.8 > pH = 7/c(H2O2) > pH = 7. Ten aromatic intermediates were formed during the degradation of LFXN, which were further degraded to F-, NH4+, NO3-, CO2 and H2O. This study provides a promising approach for efficiently treating LFXN antibiotic wastewater by pulsed electrochemical oxidation with a BDD electrode without adding H2O2.
This study was to develop biogranules using a sequencing batch reactor (SBR) and to evaluate the effect of pineapple wastewater (PW) as a co-substrate for treating real textile wastewater (RTW). The biogranular system cycle was 24 h (2 stages of phase), with an anaerobic phase (17.8 h) followed by an aerobic phase (5.8 h) for every stage of the phase. The concentration of pineapple wastewater was the main factor studied in influencing COD and color removal efficiency. Pineapple wastewater with different concentrations (7, 5, 4, 3, and 0% v/v) makes a total volume of 3 L and causes the OLRs to vary from 2.90 to 0.23 kg COD/m3day. The system achieved 55% of average color removal and 88% of average COD removal at 7%v/v PW concentration during treatment. With the addition of PW, the removal increased significantly. The experiment on the treatment of RTW without any added nutrients proved the importance of co-substrate in dye degradation.
This study analyzes the regional implications of China's 2017 import ban on plastic waste by examining U.S. census data. A statistically significant decrease in total U.S. plastic waste exports was found, dropping from about 1.4 million tons to 0.6 million tons in the post-ban period. California remained the top exporter, throughout both pre- and post-ban periods, while South Carolina exhibited the highest per capita exports. Malaysia emerged as the largest importer of U.S. plastic waste, followed by Vietnam, Indonesia, and Thailand. The ban also led to a change in the composition of the exported plastic waste. Ethylene polymers increased from 32.6% of total exports in the pre-ban period to 46.9% in the post-ban period. Other plastics (vinyl chloride polymers, styrene polymers, and for plastics not elsewhere specified or included) decreased from 67.4% of total exports in the pre-ban period to 53.1% in the post-ban period. Moreover, we found that exporting plastic waste has significant environmental and human health impacts. For example, the Global Warming Potential (GWP) decreased from 20 million tons CO2-eq in the scenario where 100% of plastics are exported, or 25 million tons exported from the U.S. since 2002, to -11.1 million tons CO2-eq in the scenario where 100% of plastics are treated domestically. Transportation exacerbates these impacts for exported waste scenarios, increasing to 5.4 million tons CO2-eq when plastics are exported by ship while decreasing to 0.9 million tons CO2-eq for domestic treatment. Although exporting plastic waste is initially cost-effective, our study highlights that investing in domestic waste management can yield significant long-term benefits, considering the environmental and public health impacts. Therefore, it is crucial to prioritize context-specific solutions to address the challenges of the evolving global plastic waste landscape.
Three-dimensional heteroatom-doped graphene presents a state-of-the-art approach for effective remediation of pharmaceutical wastewater on account of its distinguished adsorption and physicochemical attributes. Amitriptyline is an emerging tricyclic antidepressant pollutant posing severe risks to living habitats through water supply and food chain. With ultra-large surface area and plentiful chemical functional groups, graphene oxide is a favorable adsorbent for decontaminating polluted water. Herein, a new boron-doped graphene oxide composite reinforced with carboxymethyl cellulose was successfully developed via solution-based synthesis. Characterization study revealed that the adsorbent was formed by graphene sheets intertwined into a porous network and engrafted with 13.37 at% of boron. The adsorbent has a zero charge at pH 6 and contained various chemical functional groups favoring the attachment of amitriptyline. It was also found that a mere 10 mg of adsorbent was able to achieve relatively high amitriptyline removal (89.31%) at 50 ppm solution concentration and 30 °C. The amitriptyline adsorption attained equilibrium within 60 min across solution concentrations ranging from 10 to 300 ppm. The kinetic and equilibrium of amitriptyline adsorption were well correlated to the pseudo-second-order and Langmuir models, respectively, portraying the highest Langmuir adsorption capacity of 737.4 mg/g. Notably, the predominant mechanism was chemisorption assisted by physisorption that contributed to the outstanding removal of amitriptyline. The saturated adsorbent was sufficiently regenerated using ethanol eluent. The results highlighted the impressive performance of the as-synthesized boron-doped adsorbent in treating amitriptyline-containing waste effluent.
This work investigates the use of novel BiOI@ZIF-8 nanocomposite for the removal of acetaminophen (Ace) from synthetic wastewater. The samples were analyzed using FTIR, XRD, XPS, DRS, PL, FESEM-EDS, and ESR techniques. The effects of the loading capacity of ZIF-8 on the photocatalytic oxidation performance of bismuth oxyiodide (BiOI) were studied. The photocatalytic degradation of Ace was maximized by optimizing pH, reaction time and the amount of photocatalyst. On this basis, the removal mechanisms of the target pollutant by the nanocomposite and its photodegradation pathways were elucidated. Under optimized conditions of 1 g/L of composite, pH 6.8, and 4 h of reaction time, it was found that the BiOI@ZIF-8 (w/w = 1:0.01) nanocomposite exhibited the highest Ace removal (94%), as compared to that of other loading ratios at the same Ace concentration of 25 mg/L. Although this result was encouraging, the treated wastewater still did not satisfy the required statutory of 0.2 mg/L. It is suggested that the further biological processes need to be adopted to complement Ace removal in the samples. To sustain its economic viability for wastewater treatment, the spent composite still could be reused for consecutive five cycles with 82% of regeneration efficiency. Overall, this series of work shows that the nanocomposite was a promising photocatalyst for Ace removal from wastewater samples.
Phytoremediation is a biological remediation technique known for low-cost technology and environmentally friendly approach, which employs plants to extract, stabilise, and transform various compounds, such as potentially toxic elements (PTEs), in the soil or water. Recent developments in utilising chelating agents soil remediation have led to a renewed interest in chelate-induced phytoremediation. This review article summarises the roles of various chelating agents and the mechanisms of chelate-induced phytoremediation. This paper also discusses the recent findings on the impacts of chelating agents on PTEs uptake and plant growth and development in phytoremediation. It was found that the chelating agents have increased the rate of metal absorption and translocation up to 45% from roots to the aboveground plant parts during PTEs phytoremediation. Besides, it was also explored that the plants may experience some phytotoxicity after adding chelating agents to the soil. However, due to the leaching potential of synthetic chelating agents, the use of organic chelants have been explored to be used in PTEs phytoremediation. Finally, this paper also presents comprehensive insights on the significance of using chelating agents through SWOT analysis to discuss the advantages and limitations of chelate-induced phytoremediation.
The spatial and temporal distributions of trace metals in dissolved forms mainly result from anthropogenic and lithogenic contributions. Surface water samples (∼0.5 m) were collected monthly at respective stations from Setiu Wetland. In this study, the behaviour of trace metals in the dissolved phases along the water column from sampling sites in the Setiu Wetland, Malaysia was investigated. In addition, dissolved organic carbon (DOC) and physical parameters such as salinity, temperature, pH and dissolved oxygen (DO) of the surface water were measured in order to evaluate the relationship between trace metals fractionation with different water quality parameters. Size fractionation study of dissolved trace metals using ultrafiltration technique were also carried out and analysed using inductively coupled plasma mass spectrometry (ICP-MS). Correlation of trace metals with other measured parameters was made to furthermore understand the dynamics of trace metals and its fractionated components in this area. The concentration of dissolved trace metals was in the range of 0.001-0.16 μg/L for Cd, 0.12-2.81 μg/L for Cu, 0.01-1.84 μg/L for Pb, 3-17 μg/L for Fe and 1-34 μg/L for Zn, suggesting the input of anthropogenic sources for trace metals such as municipal, industrial, agricultural and domestic discharge. The periodic monitoring and evaluation of trace metals in wetlands and protected tropical areas is highly recommended.
Innovative solutions are needed to limit environmental effect and optimise resource use as food waste generation rises worldwide. This study investigates the potential of upcycling food waste from fresh markets using Black Soldier Fly (Hermetia illucens) larvae (BSFL) as a sustainable approach. This study explored four fresh market food waste substrates for BSFL bioconversion: discarded fish waste (FI), slaughtered chicken waste (CHI), vegetable waste (VEG), and a 1:1:1 combination of all three (MIX). Soybean curd residue (SCR) was treated as the control substrate. The effects on larval growth, nutritional content, and waste bioconversion rates were examined. The larvae growth rate was strongly impacted by waste type, with BSF-fed CHI and MIX gaining 18.0 and 16.7 mg/d, respectively, followed by BSF-fed with SCR (12.2 mg/d), FI (8.9 mg/d) and VEG (7.6 mg/d). The waste type did not substantially alter BSFL length. The survival rate of the BSFL fed with the food waste studied ranges from 95 to 98.47%, with SCR being the highest. Our findings indicated that BSFL can effectively convert a variety of fresh market food waste into valuable biomass. CHI waste produced the highest larval biomass and bioconversion rate followed by MIX, SCR, FI and VEG. The different waste stream has a major influence on BSFL biomass nutrition. BSFL nutritional composition is independent of the substrate's nutritional content, indicating no direct correlation between substrate and BSFL biomass nutritional composition. SCR waste produced the highest protein content of BSFL (50.49%), followed by VEG (32.61%), MIX (32.57%), FI (31.03%) and CHI (29.06%). SCR waste also produced BSFL biomass with lowest lipid content (26.55%) compared to other waste which resulted into BSFL with lipid levels ranging from 42.92% to 53.72%. BSFL-fed with SCR is the most suitable to be used as an alternative animal's feed based on the protein and lipid levels, while defatting procedure is necessary for the other waste-fed BSFL to render it suitability as animal feed alternatives. Based on bioconversion rate, BSFL growth, and lipid content, the MIX and CHI waste might be viable substrates for future research.
Biofertilizers encompass microorganisms that can be applied to plants, subsequently establishing themselves within the plant's rhizosphere or internal structures. This colonization stimulates plant development by enhancing nutrient absorption from the host. While there is growing literature documenting the applications of microalgae-based and bacterial-based biofertilizers, the research focusing on the effectiveness of consortia formed by these microorganisms as short-term plant biofertilizers is notably insufficient. This study seeks to assess the effectiveness of microalgae-bacterial biofertilizers in promoting plant growth and their potential contribution to the circular economy. The review sheds light on the impact of microalgae-bacterial biofertilizers on plant growth parameters, delving into factors influencing their efficiency, microalgae-bacteria interactions, and effects on soil health. The insights from this review are poised to offer valuable guidance to stakeholders in agriculture, including farmers, environmental technologists, and businesses. These insights will aid in the development and investment in more efficient and sustainable methods for enhancing crop yields, aligning with the Sustainable Development Goals and principles of the circular economy.
Dealing with the current defaults of environmental toxicity, heating, waste management, and economic crises, exploration of novel non-edible, toxic, and waste feedstock for renewable biodiesel synthesis is the need of the hour. The present study is concerned with Buxus papillosa with seeds oil concentration (45% w/w), a promising biodiesel feedstock encountering environmental defaults and waste management; in addition, this research performed simulation based-response surface methodology (RSM) for Buxus papillosa bio-diesel. Synthesis and application of novel Phyto-nanocatalyst bimetallic oxide with Buxus papillosa fruit capsule aqueous extract was advantageous during transesterification. Characterization of sodium/potassium oxide Phyto-nanocatalyst confirmed 23.5 nm nano-size and enhanced catalytic activity. Other characterizing tools are FTIR, DRS, XRD, Zeta potential, SEM, and EDX. Methyl ester formation was authenticated by FTIR, GC-MS, and NMR. A maximum 97% yield was obtained at optimized conditions i.e., methanol ratio to oil (8:1), catalyst amount (0.37 wt%), reaction duration (180 min), and temperature of 80 °C. The reusability of novel sodium/potassium oxide was checked for six reactions. Buxus papillosa fuel properties were within the international restrictions of fuel. The sulphur content of 0.00090% signified the environmental remedial nature of Buxus papillosa methyl esters and it is a highly recommendable species for biodiesel production at large scale due to a t huge number of seeds production and vast distribution.
Tropical rainforests of Latin America (LATAM) are one of the world's largest carbon sinks, with substantial future carbon sequestration potential and contributing a major proportion of the global supply of forest carbon credits. LATAM is poised to contribute predominantly towards high-quality forest carbon offset projects designed to reduce emissions from deforestation and forest degradation, halt biodiversity loss, and provide equitable conservation benefits to people. Thus, carbon markets, including compliance carbon markets and voluntary carbon markets continue to expand in LATAM. However, the extent of the growth and status of forest carbon markets, pricing initiatives, stakeholders, amongst others, are yet to be explored and extensively reviewed for the entire LATAM region. Against this backdrop, we reviewed a total of 299 articles, including peer-reviewed and non-scientific gray literature sources, from January 2010 to March 2023. Herein, based on the extensive literature review, we present the results and provide perspectives classified into five categories: (i) the status and recent trends of forest carbon markets (ii) the interested parties and their role in the forest carbon markets, (iii) the measurement, reporting and verification (MRV) approaches and role of remote sensing, (iv) the challenges, and (v) the benefits, opportunities, future directions and recommendations to enhance forest carbon markets in LATAM. Despite the substantial challenges, better governance structures for forest carbon markets can increase the number, quality and integrity of projects and support the carbon sequestration capacity of the rainforests of LATAM. Due to the complex and extensive nature of forest carbon projects in LATAM, emerging technologies like remote sensing can enable scale and reduce technical barriers to MRV, if properly benchmarked. The future directions and recommendations provided are intended to improve upon the existing infrastructure and governance mechanisms, and encourage further participation from the public and private sectors in forest carbon markets in LATAM.
Water is a vital resource supporting a broad spectrum of ecosystems and human activities. The quality of river water has declined in recent years due to the discharge of hazardous materials and toxins. Deep learning and machine learning have gained significant attention for analysing time-series data. However, these methods often suffer from high complexity and significant forecasting errors, primarily due to non-linear datasets and hyperparameter settings. To address these challenges, we have developed an innovative HDTO-DeepAR approach for predicting water quality indicators. This proposed approach is compared with standalone algorithms, including DeepAR, BiLSTM, GRU and XGBoost, using performance metrics such as MAE, MSE, MAPE, and NSE. The NSE of the hybrid approach ranges between 0.8 to 0.96. Given the value's proximity to 1, the model appears to be efficient. The PICP values (ranging from 95% to 98%) indicate that the model is highly reliable in forecasting water quality indicators. Experimental results reveal a close resemblance between the model's predictions and actual values, providing valuable insights for predicting future trends. The comparative study shows that the suggested model surpasses all existing, well-known models.
Cultivation of microalgae in wastewater stream has been extensively reported, especially for simultaneous production of biolipid and wastewater treatment process. This study aimed to derive the research trend and focus on biolipid production from microalgae cultivated in wastewater by using bibliometric approach. The search strategy used in Scopus database resulted in 1339 research articles from 1990 to November 2023. Majority of publications (46%) were affiliated to China and India, showing their predominance in this field. Keywords related to the center of attention included biodiesel, biofuel, biomass and nutrient removal. Meanwhile, keyword with recent publication year, indicating the emerging research trends, revolved around the cultivation techniques and application of the system. Co-culture involving more than one microalgae species, bacteria and yeast showed promising results, while addition of nanoparticles was also found to be beneficial. Increasing exploration on the application of microalgae for treatment of saline wastewater was also reported and the carbon fixation mechanism by microalgae has been widely investigated to promote less environmental impact. Future research on these topics were suggested based on the findings of the bibliometric analyses.
In recent years, food waste has been a global concern that contributes to climate change. To deal with the rising impacts of climate change, in Hong Kong, food waste is converted into electricity in the framework of low-carbon approach. This work provides an overview of the conversion of food waste into electricity to achieve carbon neutrality. The production of methane and electricity from waste-to-energy (WTE) conversion are determined. Potential income from its sale and environmental benefits are also assessed quantitatively and qualitatively. It was found that the electricity generation from the food waste could reach 4.33 × 109 kWh annually, avoiding equivalent electricity charge worth USD 3.46 × 109 annually (based on US' 8/kWh). An equivalent CO2 mitigation of 9.9 × 108 kg annually was attained. The revenue from its electricity sale in market was USD 1.44×109 in the 1st year and USD 4.24 ×109 in the 15th year, respectively, according to the projected CH4 and electricity generation. The modelling study indicated that the electricity production is 0.8 kWh/kg of landfilled waste. The food waste could produce electricity as low as US' 8 per kW ∙ h. In spite of its promising results, there are techno-economic bottlenecks in commercial scale production and its application at comparable costs to conventional fossil fuels. Issues such as high GHG emissions and high production costs have been determined to be resolved later. Overall, this work not only leads to GHG avoidance, but also diversifies energy supply in providing power for homes in the future.
To replace the obsolete ponding system, palm oil mill effluent (POME) steam reforming (SR) over net-acidic LaNiO3 and net-basic LaCoO3 were proposed as the POME primary treatments, with promising H2-rich syngas production. Herein, the long-term evaluation of POME SR was scrutinized with both catalysts under the optimal conditions (600 °C, 0.09 mL POME/min, 0.3 g catalyst, & 74-105 μm catalyst particle size) to examine the catalyst microstructure changes, transient process stability, and final effluent evaluation. Extensive characterization proved the (i) adsorption of POME vapour on catalysts before SR, (ii) deposition of carbon and minerals on spent SR catalysts, and (iii) dominance of coking deactivation over sintering deactivation at 600 °C. Despite its longer run, spent LaCoO3 (50.54 wt%) had similar carbon deposition with spent LaNiO3 (50.44 wt%), concurring with its excellent coke resistance. Spent LaCoO3 (6.12 wt%; large protruding crystals) suffered a harsher mineral deposition than spent LaNiO3 (3.71 wt%; thin film coating), confirming that lower reactivity increased residence time of reactants. Transient syngas evolution of both SR catalysts was relatively steady up to 4 h but perturbed by coking deactivation thereafter. La2O2CO3 acted as an intermediate species that hastened the coke removal via reverse Boudouard reaction upon its decarbonation. La2O2CO3 decarbonation occurred continuously in LaCoO3 system but intermittently in LaNiO3 system. LaNiO3 system only lasted for 13 h as its compact ash blocked the gas flow. LaCoO3 system lasted longer (17 h) with its porous ash, but it eventually failed because KCl crystallites blocked its active sites. Relatively, LaCoO3 system offered greater net H2 production (72.78%) and POME treatment volume (30.77%) than LaNiO3 system. SR could attain appreciable POME degradation (>97% COD, BOD5, TSS, & colour intensity). Withal, SR-treated POME should be polished to further reduce its incompliant COD and BOD5.
Acid mine drainage (AMD) is recognized as a major environmental challenge in the Western United States, particularly in Colorado, leading to extreme subsurface contamination issue. Given Colorado's arid climate and dependence on groundwater, an accurate assessment of AMD-induced contamination is deemed crucial. While in past, machine learning (ML)-based inversion algorithms were used to reconstruct ground electrical properties (GEP) such as relative dielectric permittivity (RDP) from ground penetrating radar (GPR) data for contamination assessment, their inherent non-linear nature can introduce significant uncertainty and non-uniqueness into the reconstructed models. This is a challenge that traditional ML methods are not explicitly designed to address. In this study, a probabilistic hybrid technique has been introduced that combines the DeepLabv3+ architecture-based deep convolutional neural network (DCNN) with an ensemble prediction-based Monte Carlo (MC) dropout method. Different MC dropout rates (1%, 5%, and 10%) were initially evaluated using 1D and 2D synthetic GPR data for accurate and reliable RDP model prediction. The optimal rate was chosen based on minimal prediction uncertainty and the closest alignment of the mean or median model with the true RDP model. Notably, with the optimal MC dropout rate, prediction accuracy of over 95% for the 1D and 2D cases was achieved. Motivated by these results, the hybrid technique was applied to field GPR data collected over an AMD-impacted wetland near Silverton, Colorado. The field results underscored the hybrid technique's ability to predict an accurate subsurface RDP distribution for estimating the spatial extent of AMD-induced contamination. Notably, this technique not only provides a precise assessment of subsurface contamination but also ensures consistent interpretations of subsurface condition by different environmentalists examining the same GPR data. In conclusion, the hybrid technique presents a promising avenue for future environmental studies in regions affected by AMD or other contaminants that alter the natural distribution of GEP.
The construction industry generates a substantial volume of solid waste, often destinated for landfills, causing significant environmental pollution. Waste recycling is decisive in managing waste yet challenging due to labor-intensive sorting processes and the diverse forms of waste. Deep learning (DL) models have made remarkable strides in automating domestic waste recognition and sorting. However, the application of DL models to recognize the waste derived from construction, renovation, and demolition (CRD) activities remains limited due to the context-specific studies conducted in previous research. This paper aims to realistically capture the complexity of waste streams in the CRD context. The study encompasses collecting and annotating CRD waste images in real-world, uncontrolled environments. It then evaluates the performance of state-of-the-art DL models for automatically recognizing CRD waste in-the-wild. Several pre-trained networks are utilized to perform effectual feature extraction and transfer learning during DL model training. The results demonstrated that DL models, whether integrated with larger or lightweight backbone networks can recognize the composition of CRD waste streams in-the-wild which is useful for automated waste sorting. The outcome of the study emphasized the applicability of DL models in recognizing and sorting solid waste across various industrial domains, thereby contributing to resource recovery and encouraging environmental management efforts.