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Purpose – In this research, we have prepared activated carbon (AC) from the waste of banana peels (Musa acuminate L.) using potassium hydroxide (KOH) for carbon monoxide (CO) adsorption from motorcycle gas emission.

Design/Methodology/Approach – The activation was conducted using a chemical activator (KOH) at various concentrations of 1, 2, and 3 N for 1, 2, and 3 h, respectively. Characteristics of banana peels AC (BPAC) produced were analyzed using the Fourier-transform infra-red spectroscopy and scanning electron microscopy.

Findings – Results showed that KOH concentration and activation time strongly affected the CO adsorption and opening of the AC surface pore. There was an increase in the CO sorption when the KOH concentration was increased up to 3 N concentration. The highest CO adsorption from the emission occurred at 70.95% under KOH concentration of 3 N during the 3-h preparation.

Research Limitations/Implications – BPAC has been used as an adsorbent for only CO from motorcycle gas emission but not as an adsorbent for HC, NO, NO_x, or H₂S.

Practical Implications – BPAC can be used as the potential adsorbent for the removal of CO from motorcycle gas emission, and it is an environmental friendly, low cost, and easy to make adsorbent.

Originality/Value – In this study, the AC is made from biomass and is used in wastewater treatment, but limited studies are found on the removal of CO from motorcycle gas emission.

Heavy metals play a crucial role in the economic development of any nation. Industries utilizing heavy metals, consequently, emanate a large volume of metal-containing liquid effluents. Since metals are non-renewable and finite resources, their judicious and sustainable use is the key. Hazardous metal-laden water poses threat to human health and ecology. Apart from metals, these industrial effluents also consist of toxic chemicals. Conventional physical–chemical techniques are not efficient enough as it consumes energy and are, therefore, not cost effective.

It is known that biomaterials namely microorganisms, plants, and agricultural biomass have the competence to bind metals, in some cases, selectively, from aqueous medium. This phenomenon is termed as “metal biosorption.” Biosorption has immense potential of becoming an effective alternative over conventional methods. The authors in the present chapter have used secondary data from their previous research work and attempted to develop few strategic models through their feasibility studies for metal sustainability.

Improved production with quality, safety, and security is the biggest challenge of the food industry. Modern technologies, including robotics and automation systems, can help to cope with such issues. This chapter gives a brief view of robotics and automation for the sustainable food industry along with packaging, warehousing, distribution, marketing, and consumer services. It describes the recently implemented solutions of robotic automation in different supply chain operations and various food commodities. The benefits of robotic and automation technology for perishable and semi-perishable items have also been covered. The present research may assist the food industry professionals, supply chain managers, and academicians in implementing automation and robotics in the food industry.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

Every year, tens of millions of the 1.4 billion cars on the world’s roads are decommissioned. While the ferrous and other metals that constitute about 75% of a vehicle by weight can be readily and profitably recycled, the remaining mix of plastics, glass, composites, complex materials, fragments and contaminants are mainly destined for landfill as automotive shredder residue (ASR). For every car, approximately 100–200 kg of ASR is disposed of in landfill, posing a growing technical and environmental challenge worldwide. The recovery of the ASR for high-end application is the focus of this study, aiming to optimise the use of these valuable resources and minimise the extractive pressure for raw materials, a future green manufacturing, contributing towards a zero waste circular economy. As the dissolution of carbon into iron is a key step in the manufacture of iron-carbon alloys, the feasibility of utilizing the waste polymers within ASR as sources of carbon in different areas of pyrometallurgical processing was investigated. Polypropylene and rubber, in a blend with metallurgical coke, were used as carbonaceous substrates and the slag-foaming phenomenon was investigated via the sessile drop technique in an argon environment at 1,550°C. The results indicated the rubber/coke blend achieved significantly better foaming behaviour, and the PP/coke blend exhibited a moderate improvement in slag foaming, in comparison to 100% metallurgical coke. The overall results indicated the incorporation of ASR had significant improvement in foaminess behaviour, increasing furnace efficiency.

Food fraud has vexed the food industry throughout history. Today, it is still a present and multidimensional problem affecting all parts of the food industry. Food fraud encompasses adulteration, counterfeit, diversion of products outside of intended markets, over-run, simulation, tampering, theft, misrepresentation or mislabelling, malicious poisoning, bioterrorism or sabotage. It is difficult to detect and trace the source of unintentional contamination and related food safety concerns and even more difficult to detect instances of product fraud. The most common product categories that are associated with food fraud are olive oil, milk and milk-based products, fish and seafood, wine, tea, honey and organic foods. On the other hand, knowledge on what influences the occurrence of fraud in food supply chain is limited. The main research aim in this chapter is to determine key factors which influence the occurrence of food fraud within the organic supply chain, and how these factors differ between various organic marketing channel members. We focus on the application of qualitative methods for detecting key food fraud aspects including broad practical areas, such as opportunities and motivations to commit fraud, as well as the presence or lack of suitable food fraud control measures. These three key aspects are assessed to identify the perceived fraud vulnerability of the organic supply chain. The research is conducted with special attention to the context of the transition economies, since these markets require a new, comprehensive strategic approach to preventing and detecting food fraud and adulteration. The entire analysis is conducted on the Serbian market.

Although there have been extensive studies on the hydrological and erosional impacts of logging, relatively little is known about the impacts of conversion into agricultural plantation (namely rubber and oil palm). Furthermore, studies on morphological impacts, sediment-bound chemistry and forensic attribution of deposited sediment to their respective sources are scarcer. This chapter introduces the potential for using the multi-proxy sediment fingerprinting technique in this context. Featuring pilot projects in two major flood-prone river systems in Malaysia, the studies explore application of geochemistry-based sediment source ascription. The geochemical signatures of sediment mixtures on floodplains were compared to sediments from upstream source tributaries. The tributaries were hypothesised to have different geochemical signatures in response to dominant land management. The first case study took place in the Segama River system (4,023 km²) of Sabah, Malaysian Borneo where a mixture of primary forest, logged-forests and oil palm plantations were predominant. The second case study was in the Kelantan River Basin (13,100 km²) with two major tributaries (Galas River and Lebir River) where logged-forests and rubber and oil palm plantations are dominant land-uses. Both case studies demonstrated the applicability of this method in ascribing floodplain deposited sediment to their respective upstream sources. Preliminary results showed that trace elements associated with fertilisers (e.g. copper and vanadium) contribute to agricultural catchment signatures. Alkaline and alkaline-earth elements were linked to recently established oil palm plantations due to soil turnover. Mixing model outputs showed that contributions from smaller, more severely disturbed catchment are higher than those from larger but milder disturbed catchments. This method capitalises on flood events to counter its adverse impacts by identifying high-priority sediment source areas for efficient and effective management.