This study investigates the potential of leaf and various organic waste composts as bio-organic fertilizers using 16S rRNA metagenomics. The microbial richness and diversity analysis, employing alpha and beta diversity indices, reveal substantial variations influenced by organic substrates during composting. The leaf compost had a high total OTU (70,554) but low microbial diversity (Chao 1 index = 272.27). The kitchen waste compost had the highest microbial diversity (Chao 1 index = 429.18). Positive correlations between microbial biomass, diversity, and compost quality highlighted the pivotal role of microbial activity. The beneficial genera identified across all the bio-composts were Lactobacillus, Leuconostoc, Sphingobacterium, Paenibacillus, Pseudomonas, and Clostridium. Some pathogenic genera were also detected in all the composts analyzed, viz. Prevotella, Agrobacterium, Fusobacterium, and Streptococcus. Nonetheless, the ratio of beneficial to the pathogenic genera was generally high in all compost, highlighting the enrichment with beneficial microorganisms. The leaf compost demonstrated the highest proportion of beneficial genera, about 92%, indicating significant bio-fertilizing potential, with a low % level of pathogenic genera of about 3%. Thus, the leaf compost has excellent potential to be used as a bio-organic fertilizer. Understanding the microbial composition of organic waste composts is crucial for its application as bio-fertilizer for promoting sustainable agriculture.

This detailed study assessed heavy metal contamination of sediments/soil near central India’s largest copper mining area using 38 sampling sites within 10 km of the mine using atomic absorption spectroscopy. This study utilized multivariate pattern recognition methods, namely hierarchical clustering analysis (HCA) and principal component analysis (PCA), for source identification. Twelve parameters, i.e., copper (Cu), manganese (Mn), cobalt (Co), zinc (Zn), nickel (Ni), lead (Pb), organic matter (OM), cation exchange capacity (CEC), soil pH, distance (D), and elevation (E) were analyzed. The hierarchical cluster analysis (HCA) was used to analyze the sample sites with similar metal contamination and principal component analysis (PCA) was used to analyze the relationship between the parameters as well as to identify sources of heavy metal pollution. Three major pollution hotspots were detected by AHC and were classified as unpolluted/low pollution sites (UPS: mean concentration factor of 1.35 for Cu), highly polluted sites (HPS: mean concentration factor of 22 for Cu), and extremely polluted sites (EPS: mean concentration factor of 74 for Cu). PCA revealed three hidden factors/components, namely PC1 (explaining 38% of the variability), PC2 (18% of the variability), and PC3 (14% of the variability). Metals showed strong positive loading in PC1, explaining the highest variability. The mean content of Cu in soil/sediment samples was 502.526 mg/kg. The mean copper content was 10 times higher than the natural crustal value of 45mg/kg, indicating severe pollution in several sites around the study area. Mapping of copper contamination was conducted to reveal the spatial distribution of copper contamination using QGIS. This study exposes the heavy metal contamination level in surface sediments/soil and the effectiveness of pattern recognition techniques for the assessment of multivariate datasets in discerning spatial disparities and identifying the contamination causes.

In the face of the rapid rise in global waste production and the pressing need to shift towards sustainable energy options, advanced Waste-to-Energy (WtE) technologies have emerged as a highly promising solution. These innovative technologies effectively utilize waste as a valuable resource, presenting a viable pathway for sustainable energy recovery and making a substantial contribution to the principles of the circular economy paradigm. This review provides a comprehensive overview of advanced WtE technologies, including thermal, biological, and chemical methods, such as gasification, pyrolysis, plasma arc gasification, anaerobic digestion, fermentation, transesterification, and hydrothermal carbonization. The efficiency of these technologies is evaluated based on their energy recovery potential, environmental impact, and economic feasibility. Case studies on successful implementations of advanced WtE technologies are analyzed to highlight their practicality and effectiveness. Finally, the paper addresses technical, regulatory, and policy challenges in this field and provides future perspectives. The objective is to underscore the role of advanced WtE technologies in achieving a sustainable and resource-efficient circular economy.

Sawdust, a major waste product of the forestry industry, is accumulating along the Lagos Lagoon in Lagos, Nigeria, without it being effectively managed. Besides its use in The saccharification of sawdust could contribute to the development of renewable energy sources and feedstock for bioproduct development. The process is, however, not that straightforward as variables such as the type of cellulase enzyme, pretreatment of the cellulose substrate, and optimizing of cellulase to cellulose ratio are a few that need to be optimized for the process to be effective in terms of glucose production.manufacturing sound-absorbing boards to reinforce concrete beams and for energy purposes, its potential as a renewable energy source and feedstock for bio-product development has not yet been realized. Cellulose, a glucose biopolymer and structural component of cellulose can be hydrolyzed by a hydrolytic enzyme known as cellulase. During the process, the enzyme breaks the B-1,4-glucosidic bond, which keeps the glucose units together, and by acting on this bond, numerous glucose units are released. As part of sawdust, the cellulose molecule is not freely available for the degradation action of the cellulase enzyme as it is strongly associated with lignin, which acts as bio-glue, keeping cellulose and hemicellulose together. Delignification is an effective technique that was used to make the sawdust from ten different trees along the Lagos Lagoon in Nigeria more susceptible to saccharification by cellulase isolated from the fungus Aspergillus niger. Delignified and non-delignified sawdust masses between 2 mg and 10 mg were incubated with the A. niger cellulase solution (2 mg.mL-1), whereafter, the amount of sugar produced by the cellulase action was determined. The percentage saccharification of each sawdust material was also linked with the amount of sugar produced during cellulase action. From these investigations was concluded that delignification increased sugar production when almost all the masses of different sawdust materials were degraded. It was also observed that the ratio of sawdust mass to enzyme concentration is an important variable that influences the effectiveness of the saccharification process. The percentage saccharification of the various sawdust materials was also determined, and it indicated that the highest percentage of saccharification was not obtained when the highest amount of sawdust was degraded, producing the highest amount of sugar.

This article examines the potential for artificial intelligence (AI), blockchain, and the Internet of Things (IoT) to advance sustainability. Through a literature review and critical analysis, the study evaluates the possible advantages, difficulties, and opportunities of utilizing these technologies to support a sustainable future. The research study emphasizes how effective AI is at streamlining resource management, increasing system efficiency, and optimizing energy use. It focuses on the potential of blockchain to improve supply chain accountability and transparency, and it also discusses the game-changing potential of IoT to improve resource management. However, some issues must be resolved, including excessive costs, technological difficulties, data privacy concerns, and social repercussions. The essay advocates creating multidisciplinary research programs, funding R&D, and supporting collaborative relationships. It also suggests creating sustainable implementation plans, prioritizing ethical issues and data governance, and encouraging information exchange and awareness. By accepting these proposals, stakeholders may leverage the promise of green technology and innovation to build a sustainable future. It is also clear that the Internet of Things (IoT) can potentially optimize resource management. Real-time data on a variety of topics, including traffic conditions, air and water quality, and water management, can be provided through IoT-enabled sensors. Cities may reduce traffic, increase energy efficiency, enhance environmental conditions, and encourage sustainable water management techniques by utilizing this data to inform their decisions. However, serious consideration must be given to data privacy, security, scalability, and interoperability issues to ensure IoT solutions’ ethical and efficient adoption. Despite their enormous potential, the paper acknowledges the difficulties and constraints in implementing these technologies. Significant obstacles include high implementation costs, complex technical requirements, and the requirement for adequate data privacy and security safeguards. A sustainable and inclusive future also requires resolving ethical issues, including algorithmic prejudice, social fairness, and equitable access to technology. The report recommends encouraging cooperative relationships between academia, business, government, and communities to address these issues. Research and development investments are required to evaluate these technologies’ practical use, scalability, and economic viability. In addition, multidisciplinary research initiatives can comprehensively comprehend green technology and innovation’s social, economic, and environmental effects. It has been concluded that there is great potential for future technologies, such as AI, blockchain, and IoT, to advance sustainability. Stakeholders can use these technologies’ revolutionary potential to build a sustainable future by resolving obstacles, promoting collaboration, and doing additional research. To ensure the ethical and successful application of green technology and innovation for the benefit of the environment and future generations, it is essential to prioritize ethical considerations, establish sustainable implementation strategies, and foster information exchange and awareness.

Various wastes can be utilized to produce activated carbon, one of the wastes that can be utilized is nutmeg shell (Myristica fragrans). Activated carbon from nutmeg shells (Myristica fragrans) was used in this study to reduce the content of Pb(II) and Cu(II) ions in liquid waste. This research utilized the adsorption method with the batch system to determine the optimum contact time, optimum pH, and adsorption capacity. The characterization of activated carbon was done by Scanning Electron Microscopy (SEM) and Surface Area Analyzers (SAA). The content of Pb(II) and Cu(II) ions in the filtrate after adsorption was analyzed using an atomic absorption spectrophotometer (AAS). The results of SEM analysis showed that the carbon surface was cleaner and had more open pores after the activation process than before activation. The carbon surface area is 19.6243 m2.g-1. From the results of AAS analysis, the optimum time and pH for Pb(II) and Cu(II) ions was 40 min at pH 5 and 70 min at pH 4. With the Freundlich isotherm method, the adsorption capacity of the adsorbent for Pb(II) ions was 9.6028 mg.g-1 and Cu(II) ions was 0.035 mg.g-1, and the adsorption effectiveness on liquid waste for Pb and Cu metals was 1.9454 mg.g-1 and 0.4251 mg.g-1, respectively. The results showed that activated carbon from the nutmeg shell (Myristica fragrans) was able to reduce the levels of Pb(II) and Cu(II) ions in liquid waste.

In this study, the aridity index (AI) based on gridded climate data was validated for defining aridity and classifying aridity zones in Iraq through comparison with the results obtained by the station-based aridity index. Gauge-based gridded climate data taken from Climatic Research Unit Timeseries (CRU TS) were used to determine the annual value of four aridity indices (Lang, De Martonne, Ernic and UNEP AI) over the period 1998-2011. The results showed that the aridity distribution maps derived using grid-based aridity indices were reasonably close to those found using station-based ones. The four aridity indices properly identified similar aridity (dryness) classifications in both the station-based and grid-based aridity maps. The area percentage of each aridity class predicted by grid-based AIs was also compared with that obtained by the station-based AIs. The results showed that the variances between the area percentages predicted by grid-based AIs and those estimated using station-based AIs are fairly slight. The Lang AI exhibited the least variance (0.4%) while the De Martonne AI had the biggest variance (-4.8%). Despite these minor variances, it is however possible to conclude that the grid-based aridity index classified the aridity zones of Iraq as properly as the station-based aridity index did.

Oil spills in the Niger Delta could exert environmental pressures on the soil component. We investigated the impacts of oil spills and the effect of the Enhanced Natural Attenuation (ENA) remediation method on contaminated soil and resident microbial populations in the Odhiaje community in Rivers State, Nigeria. Soil samples for microbiological studies were collected weekly during a 17-week remediation period, while those for edaphic parameters were taken before and after remediation, all at 4 sampling points (SPs). Serial dilution of the oil-impacted soils for microbial density enumeration was carried out according to standard methods. Results revealed that mean concentrations of Total Petroleum Hydrocarbon Contents (THC) (Sig.value = 0.009), SO42- ions (Sig.value = 0.001), and sand compositions (Sig.value = 0.045) all differed markedly across the sampling points at p<0.05. Mean levels of EC (Sig.tvalue = 0.039) and ΣN (Sig.tvalue = 0.058) & K+ ions (Sig.tvalue = 0.004) differed significantly before and after the remediation exercise at the 95% confidence interval. Application of nutrients was rapidly accompanied by microbial population increases, leading to the consumption of oil contaminants in soils to levels comparable to control over the remediation period. Total Heterotrophic Bacteria counts correlated with pH (r = 0.501) and SO42- ions (r = 0.500) (p<0.05), and K+ ions (r = -0.800) (p<0.01); Total Heterotrophic Fungi correlated with pH (r = 0.520) (p<0.05), and Mg2+ ions (r = 0.820) (p<0.01); Hydrocarbon Utilizing Bacteria correlated with available P (r = 0.530) and silt composition (r = -0.504) (p<0.05), and K+ (r = 0.626) and Mg2+ ions (r = 0.733) (p<0.01); and Hydrocarbon Utilizing Fungi correlated with K+ (r = 0.500) & Mg2+ ions (r = 0.506) (p<0.05). Results indicate improvement in C/N ratios and effectiveness of the current cost-effective bioaugmentation technique in the restoration of arable soil productivity in the Odhiaje community.

In the present study, biodegradation of polycyclic aromatic hydrocarbons (PAHs) was examined using two fungal strains, namely P. chrysosporium and P. citrinum, isolated from locally contaminated soil. These two fungal strains were compared based on degradation properties under standardized conditions (pH 7.0, temperature 30oC, carbon source yeast extract) using PAH sole and a mixture of five different PAHs. In liquid media, PAH degradation was higher as compared to spiked soil by P. chrysosporium, followed by P. citrinum. In liquid culture, maximum degradation was 96.13% phenanathrene, 86.34% fluoranthene, 72.75% pyrene, 52.25% chrysene, and 40.16% benzo(a)pyrene by P. chrysosporium. PAH degradation in spiked soil was 78.5% phenanthrene, 65.91% fluoranthene, 61.73% pyrene, 48.2% chrysene, and 26.82% benzo(a)pyrene within 28 days by P. chrysosporium. Both local fungal isolates showed potential for degradation of PAHs alone and in PAH mixtures.

The main purpose of the study is to identify the thin-bed reservoirs of the Eastern Folded Belt (Sylhet and Bandarban) and characterize them with diligence. A detailed qualitative and quantitative analysis has been carried out. It is based on thin-section petrographic analyses of sandstone samples. These samples are from the reservoir horizons of the Sylhet region and Bandarban region fields. The purpose of this analysis is to characterize the textural and mineralogical properties. Additionally, it aims to evaluate the post-depositional diagenetic changes. The results obtained from the field and laboratory analysis are studied extensively to characterize the thin-bed reservoirs. Samples from the Sylhet area are medium-coarse-grained, fairly sorted, tight packing, submature-mature sublithic characteristics. Contrarily, samples from the Bandarban region are mature-submature sublithic arenites, which are fine-medium-grained, moderately well-sorted, and moderately loosely packed. Despite the similarity of the detrital elements (quartz, feldspar, lithic grains, mica, etc.) in the two areas, silica cementation is more frequent in Sylhet region samples than early carbonate cementation in Bandarban region samples. Comparatively speaking, the sediments in the Sylhet region are more compact than those in the Bandarban region. The most important outcome of this study is that the thin bed of the unconventional reservoir and the conventional reservoir are in close proximity. The Thin-bed reservoir units of the Eastern Folded Belt are found to be medium to fine-grained and well sorted, with frequent alteration of sand-shale with the prevalence of parallel bedded sandstone. Average porosity is 4% to 12%, and pore spaces are interconnected. So, the permeability rate is good enough to flow the hydrocarbon through these pore spaces. Most importantly, the thin bed and tight reservoir (average porosity 4% to 12%, but pore spaces are not interconnected) are not more prominent than 1 meter or 2 meters. Subsequently, though the vertical thickness is not so high, they keep up a momentous tirelessness of horizontal progression. On the contrary, at whatever point it comes to a conventional reservoir, the vertical thickness is higher than that of the unconventional reservoir. But their lateral persistence is not as long as unconventional ones.