Plastic Bottle Recycling Research Articles

RECYCLING OF ASPHALT PAVEMENT AGGREGATES AND WASTE PLASTIC BOTTLES IN ADDITION TO HOT-MIX ASPHALT PRODUCTION: ADEQUATE RECYCLING RATE

This study focused on the recycling of asphalt pavement aggregates and waste plastic bottles (WPB) in addition to hot-mix asphalt (HMA) production. To achieve this objective, non-probable sampling methods were used to gather samples from the study locations. Crushed stone aggregate (CSA), bitumen, mineral filler, reclaimed asphalt pavement aggregate (RAPA), and WPB were the ingredients employed based on the requirements in the standard specification for asphalt concrete production. Initially, the Marshall Stability Test was then carried out using CSA with 6% and bitumen levels of 4.0, 4.5, 5.0, 5.5, and 6% by weight of the total mix to ascertain what the bitumen content should be with RAPA with replacement rates of 10, 20, and 30% and that of WPB with 2, 6, 8, 10, 12, and 14%. In the Marshall Stability Test, which consisted of three trials of 195 samples and 60 mix designs, 45 were for the control mix and 150 for the replacement proportion. In the Marshall Stability Test, the ideal value for CSA was 5.1%; for RAPA, 5.1%; and for WPB, 7.7, 5.5, 5.4, 5.0, 5.5, and 5.4% optimum bituminous content (OBC). 20% RAPA and 10% WPB by weight of OBC in the stability-modified asphalt mix satisfies Ethiopian Road Authority (ERA) and American Society for Testing and Material (ASTM) specifications for all qualities tested. Finally, for improved asphalt mix performance, a combined 70% CSA, 20% RAPA, and 10% WPB should be used in asphalt mixes at 5.0% OBC. These experimental Marshal Stability Test findings satisfy the necessary specifications of ERA and ASTM for all tests used in HMA production. Thus, this proportion is strongly advised.

Turning Trash into Treasure: Developing an Intelligent Bin for Plastic Bottle Recycling

Turning Trash into Treasure: Developing an Intelligent Bin for Plastic Bottle Recycling

Sustainable plastic bottle recycling: employing zinc-deposited SBA-15 as a catalyst for glycolysis of polyethylene terephthalate

<abstract> <p>Novel catalysts for recycling PET bottles into monomers have been developed by depositing zinc onto the surface of SBA-15, mitigating ZnO catalyst agglomeration in glycolysis separation processes to enhance reaction yields. Various zinc compounds (Zn(OAc)<sub>2</sub>, ZnCl<sub>2</sub>, and ZnSO<sub>4</sub>) were employed as substrates for catalyst design on the porous, high-surface-area material SBA-15 <italic>via</italic> impregnation. The presence of distinct Zn species on SBA-15 was confirmed through XRD and EDS analyses. The acidity of the catalyst, a crucial factor in the PET glycolysis process, was assessed using different Zn-containing precursors. NH<sub>3</sub>-TPD measurement has revealed the highest acidity in ZnCl<sub>2</sub>, followed by Zn(OAc)<sub>2</sub> and ZnSO<sub>4</sub>, respectively. Glycolysis reactions with a PET:EG ratio of 1:5 and a 1% catalyst at 200℃ for 2 hours revealed the catalytic efficacy of zinc-deposited compounds in the sequence ZnCl<sub>2</sub> > Zn(OAc)<sub>2</sub> > ZnSO<sub>4</sub>. Surprisingly, the ZnCl<sub>2</sub> catalyst produced the highest yield of <italic>bis</italic>-2-hydroxyethyl terephthalate (BHET) at 75% and displayed exceptional recycling capability over three cycles, contributing significantly to resource recovery objectives aligned with the Sustainable Development Goals (SDGs).</p> </abstract>

A Prototype of Smart Plastic Bottle Recycle Machine Using IoT

The growing concern over plastic pollution and its adverse impact on the environment has prompted the development of innovative solutions to address the issue effectively. Improper disposal of plastic bottles leads to environmental pollution. This paper presents the design and implementation of a prototype of smart plastic bottle recycle machine, integrating the Internet of Things (IoT). The Arduino board is used to control the machine. The smart plastic bottle recycling machine incorporates the ESP8266 and a Wi-Fi enabled system-on-chip (SoC) module used to develop IoT embedded applications. The utilization of IoT technology enables seamless real-time data transmission, allowing for efficient communication with the central system and simpliying remote monitoring and management processes. The IoT-enabled sensors and cameras capture information about the plastic bottles, such as their material, size, and condition. Thus, it makes recycling easy and satisfying, which motivates people to get involved in recycling activities. Moreover, implementing a point system that rewards individuals for their recycling efforts not only serves as an extra motivation for users, but also encourages them to actively participate in the preservation of the environment. Therefore, this prototype demonstrates the potential to foster sustainable recycling practices, which is a promising first step towards a future that prioritizes environmental consciousness

Plastic waste and fish landed by beach seine fishers in coastal Ghana.

Baseline data on plastic landing by fishers and monitoring of this is important in evaluating the success of plastic waste management efforts. This study investigated plastic and fish landed by beach seine fishers in Ghana together with the rate of plastic deposition on an adjoining beach. Plastic constituted 31.6% of the total catch and 41.7% of the fish landed by weight. There were significant differences between the average weight of fish (139.58 ± 53.6 kg) and plastic (65.73 ± 14.6 kg) landed per fishing session and the catch per unit effort of fish (183.4 ± 76.7 kg/day) and plastic (88.4 ± 35.2 kg/day). The mean weight of plastic landed per fishing session was higher than the mean weight of each of the 26 species of fisheries. The rate of plastic deposition on the beach was 8.1 ± 2.5 plastic items per m2 per tidal cycle or 0.35 ± 0.11 kg plastic per m2 per tidal cycle with food packs and tableware dominating the deposited plastic. The results suggested ongoing water sachets and plastic bottle recycling in Ghana are yielding results and calls for targeted efforts in plastic food packs and tableware management.

Blockchain-based tokenization and its impact on plastic bottle supply chains

Over the past few decades, industrial plastic production has been experiencing exceptional growth. The durability, lightness, stability, and low cost of conventional plastic materials are clear benefits that explain their popularity and application variety. However, these advantages are offset by complex after-use processes in which post-consumer plastic waste is either recycled, used for energy recovery, or dumped in landfills, where it breaks down into harmful microplastics. In practice, existing approaches to incentivize end-consumers for the proper collection of plastic bottle waste pose certain barriers and weaknesses. In this study, we propose blockchain-based tokenization as an alternative incentive system and investigate its impact on plastic bottle supply chains (SC). Together with industry partners, including Coca-Cola HBC, we first developed a process model of a circular plastic bottle SC based on blockchain tokenization and then implemented it in an empirical pilot study. Here, we tested different token-based incentives (i.e., donations, lottery tickets, and gamification) for their attractiveness among end-consumers to enhance collection efforts of plastic bottles. We then developed a system dynamics model where we used empirical data from the pilot study to analyze the impact of incentivization via blockchain-based tokenization on a circular plastic bottle SC. The insights from the pilot study demonstrate the practical and technical feasibility of such a novel incentivization approach when implemented in a real-world setting. It was also found that token-based incentives for social purposes are most suitable for stimulating end-consumers for proper plastic bottle recycling. Furthermore, the results show the positive effects of the proposed system in terms of reduced virgin material delivery and higher collection fractions of plastic bottles.

Enabling mechanical recycling of plastic bottles with shrink sleeves through near-infrared spectroscopy and machine learning algorithms

Shrink sleeves interfere with the mechanical recycling of plastic bottles because of their poor sortability during near-infrared (NIR)-based sorting. This study aims to identify reasons for their poor sortability and to propose solutions to overcome them. Five machine learning (ML) algorithms (decision tree, random forest, support vector machine, partial least squares, and convolutional neural network) are trained on NIR spectra of sleeved and non-sleeved materials and evaluated on different test datasets to investigate the influences of different product designs and post-consumer effects on the classification process. The results show that the sortability of sleeved plastic bottles can be significantly improved by (i) avoiding printing or coloring sleeves black and sleeves with large-area printing and high shrinkage; (ii) adding sleeved bottle spectra to the ML training data; (iii) choosing optimal ML algorithms with suitable hyperparameters. With these improvements, the NIR-based sorting and thus mechanical recycling of sleeved bottles could increase greatly.

RCoins – citizens become entrepreneurs

ABSTRACT As a recent phenomenon, crowdfunding has been positively influencing entrepreneurial financing and has been leading the way to a democratization of financial opportunities for entrepreneurs and backers. With the ambition to positively impact the entrepreneurial processes in crowdfunding markets, the RCoins project evolves around the idea of all citizens becoming sustainable investors, while helping transition from a linear to a circular economy. Today, the platform users receive 1 RCoin for every recycled bottle and use their RCoins for offers and discounts or for donations to charities. The next step will be to encourage citizens to be more motivated toward plastic bottle recycling, incentivizing them via an innovative crowd-investment reward platform. As part of an entrepreneurship and innovation ecosystem, RCoins will help increase the adoption of innovation in sustainable entrepreneurship and will contribute to resolving social and environmental issues by identifying and creating entrepreneurial opportunities.

COMBINING EXTENDED PRODUCER RESPONSIBILITY (EPR) AND DEPOSIT REFUND SYSTEM (DRS) POLICY FOR HIGHER RECOVERY AND RECYCLING OF PLASTIC BOTTLES AND SACHET WATER WASTE: APPLICATION OF VENDING MACHINE AND DESIGNATED RETURN DEPOT CENTRE IN LAGOS, NIGERIA

Waste management (Plastic, PET Bottle, Can, and Glass Bottle, mostly from drink and beverage packages) is an important issue in today's world, as the volume of waste increases daily. This is especially important in developing countries like Nigeria, where there are no strong institutionalized frameworks for waste management, and as a result, increasing waste poses a threat to human well-being. Given the increase in population in these countries, it is necessary to adopt sustainable and practical solutions. Especially in Lagos, where the environmental problem of plastic waste is on the rise. Although the government is making commendable efforts to reduce the increasing volume of plastic waste in the state, they are insufficient, as it has been reported that plastic waste accounts for 15% of total waste volume according to the Lagos state waste characterization index. However, with the rise in various environmental problems caused by plastic waste, this paper proposed combining the extended producer responsibility (EPR) and deposit refund system (DRS) to achieve a high rate of recovery and recycling of waste plastic bottles and sachets. The innovative approach used green technology (vending machine) as well as indigenous knowledge are practical solutions in Lagos state. The paper is also significant because it intends to implement the developed solution in a dense urban and rural setting in Lagos, which can be replicated in other states in Nigeria. Furthermore, the components discussed in this paper are elements that allow the proposed concept to function effectively and efficiently. The proposed concept will serve as a link between Lagos and Nigeria's current linear economy and the future circular economy of plastic production and management.

Ignored microplastic sources from plastic bottle recycling

The recovery and recycling of plastic products has increased dramatically in recent years as a strategy to achieve sustainable production and minimization of plastic pollution. However, the release of microplastics during plastic recycling has received little attention. We evaluated the generation and fate of microplastics in three typical facilities which make polyethylene terephthalate (PET) flakes using post-consumer PET bottles as raw material. Microplastics, 0.1– 5.0 mm in size, were detected in production wastewater at concentrations ranging from 23.43 ± 1.04 mg/L to 1836.37 ± 31.73 mg/L, while decreased to (8.13 ± 0.42–83.83 ± 0.93) mg/L in discharge effluent and (52,166 ± 2858–68,866 ± 2500) μg/g in sludge. Interestingly, the profiles of microplastics in samples from production wastewater, effluents, and sludge showed significant differences. Although, in all three compartments, the mass of microplastics increased, and the particle number decreased with increasing particle size. Overall, the removal ratio of total microplastics from the production wastewater was 53.47 ± 4.48% to 99.56 ± 0.02% in mass, and from 90.08 ± 0.82% to 99.56 ± 0.05% in quantity. The loss of microplastics from wastewater resulted in their concentration in sludge. Factors that influence the transfer of microplastics from wastewater to sludge should be identified and utilized to maintain a high level of removal and prevent leakage of these particles into the environment.

Enhancement of Image Classification Using Transfer Learning and GAN-Based Synthetic Data Augmentation

Plastic bottle recycling has a crucial role in environmental degradation and protection. Position and background should be the same to classify plastic bottles on a conveyor belt. The manual detection of plastic bottles is time consuming and leads to human error. Hence, the automatic classification of plastic bottles using deep learning techniques can assist with the more accurate results and reduce cost. To achieve a considerably good result using the DL model, we need a large volume of data to train. We propose a GAN-based model to generate synthetic images similar to the original. To improve the image synthesis quality with less training time and decrease the chances of mode collapse, we propose a modified lightweight-GAN model, which consists of a generator and a discriminator with an auto-encoding feature to capture essential parts of the input image and to encourage the generator to produce a wide range of real data. Then a newly designed weighted average ensemble model based on two pre-trained models, inceptionV3 and xception, to classify transparent plastic bottles obtains an improved classification accuracy of 99.06%.

Respuesta agronómica del cultivo de pimiento (Capsicum annuum L) a dos condiciones de riego

he objective of this study was to evaluate the growth and development of three hybrids of the pepper crop (Capsicum annuumL), under two irrigation conditions. Currently, pepper planting under pressurized drip irrigation uses technical criteria and a high initial cost, emphasizing the current use of kondenskompressor solar drip irrigation, using conventional techniques, such as the recycling of PET plastic bottles, taking advantage of solar distillation. and that serve as a source of water for plants. As well as quantify the performance, determine the optimization of the water resource,and carry out an economic analysis. The experimental design was Divided Plots with Factorial Arrangement A x B, with six treatments and four repetitions. Plant height was evaluated at 30, 60 days; Number of fruits per plant; Diameter, length and weight of the fruit; Yield per hectare; Volume of water consumed during the vegetative cycle of the crop; Benefit-cost ratio (USD/kg/ha/year). Treatment 6 (H3R2) in all the analyzes of variance turned out to be the one with the highest average of agronomic results, with a yield.

Implementation and integration of image processing blocks in a real-time bottle classification system

A practical solution to the problems caused by the water, air, and soil pollution produced by the large volumes of waste is recycling. Plastic and glass bottle recycling is a practical solution but sometimes unfeasible in underdeveloped countries. In this paper, we propose a high-performance real-time hardware architecture for bottle classification, that process input image bottles to generate a bottle color as output. The proposed architecture was implemented on a Spartan-6 Field Programmable Gate Array, using a Hardware Description Language. The proposed system was tested for several input resolutions up to 1080 p, but it is flexible enough to support input video resolutions up to 8 K. There is no evidence of a high-performance bottle classification system in the state-of-the-art. The main contribution of this paper is the implementation and integration of a set of dedicated image processing blocks in a high-performance real-time bottle classification system. These hardware modules were integrated into a compact and tunable architecture, and was tested in a simulated environment. Concerning the image processing algorithm implemented in the FPGA, the maximum processing rate is 60 frames per second. In practice, the maximum number of bottles that can be processed would be limited by the mechanical aspects of the bottle transportation system.

Quality assessment of post-consumer plastic bottles with joint entropy method: A case study in Beijing, China

Recycling of plastic bottles is a fundamental strategy to reduce the need of fossil resources and protect global environments. The collection of post-consumer plastic bottles (PCPBs) is a key node of the recycling of plastics due to its influences on the subsequent life cycle stages. However, there is still a lack of quantitative assessment on the quality of PCPBs, especially considering the contamination and the mixture of different plastics in the collection stage. This study provides an indicator based on the joint entropy method to evaluate the quality of PCPBs in collection stage, which includes components, polymer types and colors three levels. This indicator (Quality-value) is applied to evaluate the quality of PCPBs’ collection system in Beijing city, China, which is based on an on-site survey including 27 samples gathered from 4 distribution centers and 5 collection sites. The results showed that the quality of PCPBs decreased through the collection system of Beijing, which degraded from post-consumer bottles (0.320<Q<0.325) to pre-production bottles (0.311<Q<0.312). The type of residential area is identified as a key factor of the PCPBs’ quality in collection sites. There is no obvious difference between formal and informal business models in the surveyed area. Providing three levels of quality equally weighted, colors sorting had the greatest potential to improve the quality of PCPBs compared to components and polymers sorting. We suggest that joint-entropy based quality assessment can help to manage waste collection system in an efficient way to meet the need of circular economy.

Recycled Materials for Sound Absorbing Applications

The use of recycled materials to replace natural and artificial materials represents an interesting and real possibility for all industrial sectors to contribute to the reduction of the amount of waste disposed of and non-renewable resources consumed. This study reports the results of the measurements of the sound absorption coefficient carried out on specimens obtained from the recycling of different materials. A sustainable development of our planet requires us to adopt materials recycling policies to ensure the economical use of resources. Two types of materials have been studied: material obtained from the recycling of plastic bottles, and a material obtained from the recycling of asphalt milled. Both materials showed interesting sound absorption performances covering different frequency ranges.

Comparing the environmental performance of distributed versus centralized plastic recycling systems: Applying hybrid simulation modeling to life cycle assessment

The plastic waste dilemma has gained international attention because of increased public awareness and the rise of waste import bans. Sorting and recycling technologies that deal with plastic waste streams exist but face challenges in highly dense urbanized regions such as Singapore because of high space requirements. Multiple small-scale plastic sorting and recycling facilities that are distributed closer to points of waste generation offer the possibility of increasing the recovery of plastic-waste streams in urbanized settings. To holistically quantify the environmental performance of this type of system, a life cycle assessment (LCA) is conducted to compare five different scenarios of distributed and centralized sorting and recycling of plastic bottles and takeaway containers in Singapore. A hybrid simulation model is used to simulate the complex dynamics of waste-processing systems which involves waste generation, collection scheduling, sorting, recycling, and disposal of residual materials. The results of the LCA showed that the life cycle environmental impacts to climate change, water depletion, and terrestrial ecotoxicity of the distributed scenarios were higher than the centralized scenarios by 7–30% depending on the impact category. Although the distributed scenarios had lower total travel distances, their reliance on commercial vans led to their higher environmental impacts than the centralized scenarios. The findings of this study provide motivation for future research in applying hybrid simulation models in LCAs of waste-to-resource exchange networks. The data used to carry out the hybrid simulations and the LCA are provided as Supporting Information. This article met the requirements for a Gold-Silver JIE data openness badge described at http://jie.click/badges.

Identification for Recycling Polyethylene Terephthalate (PET) Plastic Bottles by Polarization Vision

The recycling of disposed PET plastic bottles has significant meaning for environmental pollution control and resource recycling. The reuse value heavily depends on the purity of the recycled PET. In order to improve the purity of PET recycling, a new means of material identification of PET plastic bottle based on polarization vision is proposed. To identify PET plastic bottles on conveyor belt, an effective region segmentation method for plastic bottle location and feature extraction has been put forward. The polarization of the scattered light on the surface of the object contains the information of its material. To obtain robust material characteristics of the PET plastic bottle, an approximate refractive index calculation method based on the degree of polarization and phase angle is introduced. The mean, standard deviation and coefficient of variation of the approximate refractive index and intensity distribution are used to construct the feature vector. The support vector machine (SVM) algorithm was used for PET identification. The experimental results show that the mean accuracy of PET plastic bottles material identification of recycled bottles is up to 92.06%.

Experimental analysis of recycled thermoplastic material

The large number of plastics that are disposed of today in our surroundings are mostly undegradable and need imperative ways of recycling the thermoplastics like bottles, polythenes, etc. As chemical solutions to this problem are in general expensive and hazardous to the ecosystem as well so, A possible and sustainable solution is the recycling of such materials by a technique called thermo-mechanical recycling. This paper takes into consideration the thermo-mechanical recycling of plastic bottles and other thermoplastic composites which are disposed of after use. In this technique the collected waste ‘thermoplastics’ will be sent through several stages where it undergoes a cleaning process after which the waste material undergoes crushing in small fine particles and then granules are made out of the crushed waste material after this process silica colloidal additives are added to the granules while molding to restore it’s mechanical properties, thermal stability, and recyclability so that the recycled plastics can be further used in engineering applications and to ensure its physical properties after recycling some test has to be conducted like stiffness, machinability, shear stress, energy-absorbing property while impact, molding property, etc.

Plastic Bottle Cap Recycling—Characterization of Recyclate Composition and Opportunities for Design for Circularity

In line with efforts to create a circular economy of plastics, recent EU legislation is strengthening plastic bottle recycling by ambitious separate collection targets and mandatory recycled content obligations. Furthermore, explicit design requirements on the caps of bottles and composite beverage packaging have been introduced. These caps are typically made of polyethylene or polypropylene and often contain additives such as slip agents and anti-statics. Commercially available bottle cap recyclates (BCRs) as well as specifically formulated model compounds were analyzed in terms of composition by means of infrared spectroscopy, differential scanning calorimetry, and high-performance liquid chromatography. Their composition was found to be heterogeneous due to polyolefin cross-contamination, directly reflecting the diversity of cap materials present in the market. Slip agent legacy additives originating from the initial use phase were found and quantified in both commercial and model cap recyclates. This highlights the opportunity for redesigning plastic bottle caps not only in response to regulatory requirements, but to pursue a more comprehensive strategy of product design for circularity. By including considerations of polymer resin and additive choice in cap manufacturing, more homogeneous waste streams could be derived from plastic bottle cap recycling, enabling recycling into more demanding and valuable applications.

Tailoring Temporal Message Frames to Individuals’ Time Orientation Strengthens the Relationship between Risk Perception and Behavioral Intention

While health behavior theories conceptualize risk perception as a major factor motivating protective action against risk, empirical support for this widely-assumed proposition has been inconclusive. Given the inherent issue concerning the delay of desired outcomes in most health behaviors, this research proposes the congruence between temporal frame and individuals’ trait time orientation (i.e., consideration of future consequences; CFC) as an important moderator in the risk perception-behavioral intention relationship. Findings from two experiments concerning messages promoting adequate sleep (N = 227; Study 1) and plastic bottle recycling (N = 223; Study 2) showed that the relationship between risk perception and behavioral intention was significantly stronger when temporal frames and CFC were more congruent (i.e., tailored). Nuanced differences in the moderating effects of frame-CFC congruence were observed depending on how risk perception was operationalized (i.e., susceptibility only, severity only, or combination of the two). Implications for health communication message design are discussed.