Spectroscopy: A Promising Tool for Plastic Waste Management

Rapid detection of colored and colorless macro- and micro-plastics in complex environment via near-infrared spectroscopy and machine learning

To better understand the migration behavior of plastic fragments in the environment, development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary. However, most of the studies had focused only on colored plastic fragments, ignoring colorless plastic fragments and the effects of different environmental media (backgrounds), thus underestimating their abundance. To address this issue, the present study used near-infrared spectroscopy to compare the identification of colored and colorless plastic fragments based on partial least squares-discriminant analysis (PLS-DA), extreme gradient boost, support vector machine and random forest classifier. The effects of polymer color, type, thickness, and background on the plastic fragments classification were evaluated. PLS-DA presented the best and most stable outcome, with higher robustness and lower misclassification rate. All models frequently misinterpreted colorless plastic fragments and its background when the fragment thickness was less than 0.1mm. A two-stage modeling method, which first distinguishes the plastic types and then identifies colorless plastic fragments that had been misclassified as background, was proposed. The method presented an accuracy higher than 99% in different backgrounds. In summary, this study developed a novel method for rapid and synchronous identification of colored and colorless plastic fragments under complex environmental backgrounds.

Standoff Identification of Plastic Waste Using a Low-Cost Compact Laser-Induced Breakdown Spectroscopy (LIBS) Detection System

We report the standoff/remote identification of post-consumer plastic waste by utilizing a low-cost and compact standoff laser-induced breakdown spectroscopy (ST-LIBS) detection system. A single plano-convex lens is used for collecting the optical emissions from the plasma at a standoff distance of 6.5 m. A compact non-gated Czerny-Turner charge-coupled device (CCD) spectrometer (CT-CCD) is utilized to analyze the optical response. The single lens and CT-CCD combination not only reduces the cost of the detection system by tenfold, but also decreases the collection system size and weight compared to heavy telescopic-based intensified CCD systems. All the samples investigated in this study were collected from a local recycling plant. All the measurements were performed with only a single laser shot which enables rapid identification while probing a large number of samples in real time. Furthermore, principal component analysis has shown excellent separation among the samples and an artificial neural network analysis has revealed that plastic waste can be identified within ∼10 ms only (testing time) with accuracies up to ∼99%. Finally, these results have the potential to build a compact and low-cost ST-LIBS detection system for the rapid identification of plastic waste for real-time waste management applications.

Learning from Tomorrow's Recyclers: Extension of Hands-on Recycled Waste Activity

We previously developed a plastic sorting activity for high school students. In that activity, several tools were provided to separate plastic waste materials based on their physical properties while considering the time and cost for each separation step. Here, we aimed to understand the impact of this activity on the awareness of and learning about plastic sorting in a younger age group (8 to 11 years old) and explored how parental involvement influenced students' interest in the topic. The activity was part of the STEM Zone Saturday program at the University of Houston. Pre- and post-evaluations were used to assess students' understanding of plastic sorting and overall experiences. While some insights into plastic sorting were derived from previous experiences, the activity improved awareness among students, particularly regarding sorting based on physical properties. The involvement of parents encouraged exploration, discovery, and enjoyment. These findings underscore the importance of early education and community engagement in fostering sustainable practices and advancing toward a circular economy.

Monitoring CaCO3 Content in Recycled Polypropylene with Raman Spectrometry

As a commonly used filler, CaCO3 frequently finds its way into recycled polypropylene (rPP) as a contaminant during the mechanical recycling process. Given the substantial impact of CaCO3 on the properties of PP materials, close monitoring of their content is important to ensure the quality of rPP. In the present work, Raman spectrometry was employed to develop a rapid, accurate, and convenient method for determining CaCO3 content in rPP. Partial least-squares (PLS) regression was used to construct prediction models. Various spectrum pretreatment methods, including multivariate scatter correction (MSC), standard normal variate transformation (SNV), smoothing, and first derivative, were investigated to improve the model performance. In independent validation, the optimal PLS model reached an R 2 of 0.9735 and a root-mean-square error of prediction (RMSEP) of 2.7786 CaCO3 wt %. Furthermore, linear and second-order polynomial regressions, utilizing the intensity ratios of characteristic CaCO3 and PP Raman peaks, were conducted. The most effective quadratic regression curve demonstrated superior independent validation performance with an R 2 of 0.9926 and an RMSEP of 1.6999 CaCO3 wt %. Validation with recycled PP samples confirmed that the quadratic regression was more accurate and reliable to quantify CaCO3 in rPP. The observed quadratic relationship between the CaCO3 and PP Raman peak intensity ratio and the CaCO3 wt % can be attributed to the significant difference in the densities of the two components. The outcomes of this research will help to facilitate the proper recycling of PP materials.

Effective impact of nano-plastic-waste incorporated with nanotitina on the physical, mechanical and microstructural properties of white cement pastes composites for progressing towards sustainability

Plastic waste (PW) has received a lot of attention as a possible additional material for industrial and environmental applications, particularly cement and/or concrete production for a more environmentally and economically sound use of raw materials and energy sources. PW has been investigated as an inert and/or active hydraulic filler for cement and/or concrete by numerous scientists. Plastic garbage is cheap, abundant, and takes long period of time to degrade in the eco-system (soil and water). The main goal of the ongoing research is to offer safety and efficacy by partially substituting nano-plastic waste (NPW), incorporated with nano-titania (NT), for the composition of white cement (WC). Blends are built up by substitution of WC with different ratios of NPW incorporated with fixed ratios of nano-titania (1.0 wt.%). Workability, physical, mechanical and microstructural properties have gone through laboratory and instrumental analysis. The results showed improvement in the compressive strength, density and microstructure due to the effective impact of fillers. Consequently, a decrease in total porosity, whiteness reflection (Ry) and early-rapid expansion. Eventually, the outcomes may reduce the pandemic strength, especially in the external environment, and other epidemics.

Quality comparison of plastic packaging waste from different separation systems: Result enhancement with non-negative matrix factorization of FTIR spectra

Whether plastic packaging waste is disposed of in different bins (source separation, S) or in a single bin (post source separation, P) is generally assumed to impact the waste stream's quality. To elucidate this question, we evaluated the quality of LDPE, HDPE, and PP plastic waste from both separation systems (S and P) through a concise analytical strategy. The materials received similar treatment after collection (e.g., washing, NIR-sorting). A multivariate approach to ATR-FTIR spectroscopy was developed to assess their material composition and the effect of washing. Results were complemented by TGA, DSC, and py-GC/MS analysis. The material performance was investigated by a lab-scale extrusion and granulation, followed by an assessment of the mechanical properties and the melt volume rate. Our study reveals the HDPE materials to be of good quality, regardless of their source. For LDPE and PP, the P-materials are fractionally more contaminated after washing. Both PP-materials display poor material performance with highly fluctuating elongations-at-break (between 30% and 380%). S-LDPE was found to contain more polymeric impurities than P-LDPE. We conclude that the quality depends strongly on the material type and on the treatment after collection (washing, sorting). The multivariate approach to FTIR data evaluation we propose aims at simplifying the quality evaluation of polyolefin waste plastics and may serve as a basis for future work in this field.

From plastic waste to potential wealth: Upcycling technologies, process synthesis, assessment and optimization

Global plastics production has doubled since the beginning of 21st century. Efficient technology is called for plastics waste valorization. The current review provides an overview of the main waste plastic chemical upcycling technologies to produce value-added products. Various technologies including gasification and pyrolysis are under reviewed. However, several review literatures have paid attention to the details and experimental progress in these chemical upcycling techniques. In this review, we attempt to conclude the progress in a multi-scale systems-by-systems perspective. After a brief overview of the current state-of-the-art chemical upcycling techniques, larger-scale process synthesis, assessment, and optimization methodologies to address the sustainability and environmental issues are summarized. Techno-economic analysis and life cycle assessment are selected as two powerful tools for process assessment. Three particular application scenarios of optimization methodologies including experimental design, process synthesis and supply chain management are consequently introduced. Very little work on review articles have summarized the plastic waste-to-wealth process in the systems engineering perspective. Review results show that (1) gasification and pyrolysis offer promising avenues for the conversion of plastic waste into valuable products. These technologies can be integrated with other subsystems to enhance the economic and environmental performance of the overall system. (2) Response surface methodology is commonly used in experimental design and parameter optimization. It allows researchers to systematically investigate the effects of various parameters and optimize process conditions to maximize desired outputs. (3) Superstructure optimization frameworks are valuable tools for process synthesis and pathway selection in plastic waste conversion. However, the potential superstructure is pre-defined. (4) Green supply chain and multi-objective supply chain frameworks can be applied to the design of plastic waste recycling networks, taking into account both economic and environmental considerations.

Laser Ablation Plasmas and Spectroscopy for Nuclear Applications

The development of measurement methodologies to detect and monitor nuclear-relevant materials remains a consistent and significant interest across the nuclear energy, nonproliferation, safeguards, and forensics communities. Optical spectroscopy of laser-produced plasmas is becoming an increasingly popular diagnostic technique to measure radiological and nuclear materials in the field without sample preparation, where current capabilities encompass the standoff, isotopically resolved and phase-identifiable (e.g., UO and UO2 ) detection of elements across the periodic table. These methods rely on the process of laser ablation (LA), where a high-powered pulsed laser is used to excite a sample (solid, liquid, or gas) into a luminous microplasma that rapidly undergoes de-excitation through the emission of electromagnetic radiation, which serves as a spectroscopic fingerprint for that sample. This review focuses on LA plasmas and spectroscopy for nuclear applications, covering topics from the wide-area environmental sampling and atmospheric sensing of radionuclides to recent implementations of multivariate machine learning methods that work to enable the real-time analysis of spectrochemical measurements with an emphasis on fundamental research and development activities over the past two decades. Background on the physical breakdown mechanisms and interactions of matter with nanosecond and ultrafast laser pulses that lead to the generation of laser-produced microplasmas is provided, followed by a description of the transient spatiotemporal plasma conditions that control the behavior of spectroscopic signatures recorded by analytical methods in atomic and molecular spectroscopy. High-temperature chemical and thermodynamic processes governing reactive LA plasmas are also examined alongside investigations into the condensation pathways of the plasma, which are believed to serve as chemical surrogates for fallout particles formed in nuclear fireballs. Laser-supported absorption waves and laser-induced shockwaves that accompany LA plasmas are also discussed, which could provide insights into atmospheric ionization phenomena from strong shocks following nuclear detonations. Furthermore, the standoff detection of trace radioactive aerosols and fission gases is reviewed in the context of monitoring atmospheric radiation plumes and off-gas streams of molten salt reactors. Finally, concluding remarks will present future outlooks on the role of LA plasma spectroscopy in the nuclear community.

Material classification based on a SWIR discrete spectroscopy approach

A crucial yet difficult task for waste management is the identification of raw materials like plastic, glass, aluminum, and paper. Most previous studies use the diffused reflection spectroscopy for classification purposes. Despite the benefits in terms of speed and simplicity offered by modern compact spectrometers, their cost and the need for an external, wide-spectrum source of illumination create complications. To address this issue, the present paper proposes a discrete spectroscopy method that utilizes short-wave infrared (SWIR) reflectance to identify waste materials, exploiting a small set of selected wavelengths. This approach reduces the complexity of the classification data analysis and offers a more practical alternative to the conventional method. The proposed system comprises a single germanium photodetector and 10 different light emitting diodes (LEDs). The LED wavelengths are selected to maximize the system sensitivity towards a set of seven different waste materials. Using a classification strategy relying on support vector machines, the proposed methodology reaches a classification accuracy up to 98%.

Solubilization of Fully Hydrolyzed Poly(vinyl alcohol) at Room Temperature for Fabricating Recyclable Hydrogels

The versatility of poly(vinyl alcohol) (PVA) makes it extensively utilized across various industries, while the solubilization of PVA in aqueous media is essential for its applications. However, the high crystallinity of the fully hydrolyzed PVA poses a big challenge in terms of its dissolution in aqueous media at room temperature. In this work, we present a straightforward, efficient, and safe strategy to achieve this objective by the integration of inorganic additives. The crucial aspect of additives lies in the interference of hydrogen bonds and breaking of the crystal domain within PVA chains, therefore greatly enhancing the solubility. At the optimal condition, the solubility of PVA can reach up to 45 wt% at 25 °C in 4 M HBr solution. It is further proven that the solubility of PVA follows the Hofmeister series well, where the chaotropes facilitate the solubilization process. In addition, the solubility is also significantly determined by the PVA type and additive concentration. By harnessing this feature, we successfully engineer recyclable PVA hydrogels with programmable mechanical properties. The hydrogels exhibit remarkable recyclability by affording a minimum of 8 regeneration cycles without experiencing significant deterioration in mechanical properties. Collectively, this research may significantly contribute to the advancement of PVA applications.

Advancing Plastic Recycling: Challenges and Opportunities in the Integration of 3D Printing and Distributed Recycling for a Circular Economy

The concept of the circular economy has emerged as a promising solution to address the mounting concerns surrounding plastic waste and the urgent need for sustainable resource management. While conventional centralized recycling remains a common practice for plastic waste, centralized facilities may prove inadequate in handling the ever-increasing volumes of plastic waste generated globally. Consequently, exploring alternative recycling methods, such as distributed recycling by additive manufacturing, becomes paramount. This innovative approach encompasses actively involving communities in recycling practices and promotes a circular economy. This comprehensive review paper aims to explore the critical aspects necessary to realize the potential of distributed recycling by additive manufacturing. In this paper, our focus lies on proposing schemes that leverage existing literature to harness the potential of distributed recycling by additive manufacturing as an effective approach to plastic waste management. We explore the intricacies of the recycling process, optimize 3D printing parameters, address potential challenges, and evaluate the mechanical properties of recycled materials. Our investigation draws heavily from the literature of the last five years, as we conduct a thorough critical assessment of DRAM implementation and its influence on the properties of 3D printing structures. Through comprehensive analysis, we reveal the potential of recycled materials in delivering functional components, with insights into their performance, strengths, and weaknesses. This review serves as a comprehensive guide for those interested in embracing distributed recycling by additive manufacturing as a transformative approach to plastic recycling. By fostering community engagement, optimizing 3D printing processes, and incorporating suitable additives, it is possible to collectively contribute to a more sustainable future while combatting the plastic waste crisis. As progress is made, it becomes essential to further delve into the complexities of material behavior, recycling techniques, and the long-term durability of recycled 3D printed components. By addressing these challenges head-on, it is feasible to refine and advance distributed recycling by additive manufacturing as a viable pathway to minimize plastic waste, fostering a circular economy and cultivating a cleaner planet for generations to come.

Spherical DNA for Probing Wettability of Microplastics

Wettability of microplastics may change due to chemical or physical transformations at their surface. In this work, we studied the adsorption of spherical nucleic acids (SNAs) with a gold nanoparticle core and linear DNA of the same sequence to probe the wettability of microplastics. Soaking microplastics in water at room temperature for 3 months resulted in the enhancement of SNA adsorption capacity and affinity, whereas linear DNA adsorption was the same on the fresh and soaked microplastics. Drying of the soaked microplastics followed by rehydration decreased the adsorption of the SNA, suggesting that the effect of soaking was reversible and related to physical changes instead of chemical changes of the microplastics. Raman spectroscopy data also revealed no chemical transformations of the soaked microplastics. Heating of microplastics over a short period induced a similar effect to long-term soaking. We propose that soaking or heating removes air entrapped in the nanosized pores at the water-plastic interface, increasing the contact surface area of the SNA to afford stronger adsorption. However, such wetted porosity would not change the adsorption of linear DNA because of its much smaller size.

Sustainable development goals for industry, innovation, and infrastructure: demolition waste incorporated with nanoplastic waste enhanced the physicomechanical properties of white cement paste composites

The COVID-19 pandemic significantly impacts the increase in plastic waste from food packaging, masks, gloves, and personal protective equipment (PPE), resulting in an environmental disaster, if collected, processed, transported, or disposed inappropriately. Plastic waste has a very long deterioration time in the environment (soil and water), cheap, and plentiful. Additionally, construction waste disposal is a process that transfers debris to a state that does lead to any sustainable or environmental problems. The core objective of this current research work is to provide safety and efficacy by partial substitution of both ultrafine demolition waste (UDW), incorporated with nanoplastic waste (NPW), for eco-white cement (E-WC) composition. E-WC is designed by partially substituted WC with UDW (1.0, 5.0, 10.0, 15.0, and 20.0 wt.%); incorporated with NPW (1.0 and 3.0 wt.%); to adequately protect people and the environment over long periods. The context examines the high performance, physicomechanical properties and high durability of blends as presences of silica in UDW proposed a hydraulic filler material, plus; high surface area of NPW. The microstructure and workability are characterized by X-Ray Fluorescence (XRF), Scanning Electron Microscope (SEM), and Transmission Electron Microscope (TEM) measurements. The record results show greatly enhanced in the mechanical strength due to the combination of NPW and UDW (active silica). With the presence of NPW and UDW in WC matrix, the highest level of crystallization formed consequently a decrease in whiteness reflection (Ry) and total porosity. In summary, WC blend with NPW and UDW reflects better workability and energy saving qualities, which are economical and environmentally beneficial and may result in decreased construction budget and improve a long-term raw material sustainability.

Post-consumer plastic sorting infrastructure improvements planning: Scenario-based modeling of greenhouse gas savings with sustainable costs

With the increasing share of waste material recovery, household plastic waste is one of the biggest problems. In most countries, mainly manual sorting is used. Meanwhile, new automated technologies are being developed to expand the range of classifiable types to increase material recovery. The overall automation of the sorting process can help the EU's established recycling targets to be effectively met. However, the new technologies are feasible only in the case of large-capacity centers, which must be conveniently located in the existing infrastructure. This paper presents a two-stage model aiming to modernize the current sorting infrastructure for plastic waste. The approach uses multi-criteria optimization to minimize environmental impact at a reasonable price. The result is the optimal location of new automatic sorting centers, and waste stream flows using existing manual sorting facilities. The model is applied through an initial case study inspired by the Czech Republic data. Optimization output proposes four new automatic sorting lines with a total capacity of 158 kt per year. In most cases, manual sorting is used to reduce the transported weight of plastic waste, while automatic sorting lines separate the remaining, hardly recognized part. More than 60% of separately collected plastic is sorted and determined for material recovery.

Packaging Weight, Filling Ratio and Filling Efficiency of Yogurt and Relevant Packagings Depending on Commercial Packaging Design, Material, Packaging Type and Filling Quantity

Yogurt is a diverse dairy product category. It is available in different packaging designs made of different materials. To identify potential for improvement for these packagings, a better understanding about used materials and packaging efficiencies is necessary. For this study, 150 dairy products and some yogurt relevant desserts were bought from various supermarkets, street markets and discounters in the Munich region (Germany) in spring 2022. Commercial types of packaging are cups, buckets, pouches, bottles, glass packagings and bricks. The filling ratio of most packagings is above 70%, the rest of the volume is headspace. Poly(1-methylethylene) (PP) and poly(1-phenylethene) (PS) dominate as main materials for the different types of packaging. For bottle packagings, poly(ethylene terephthalate) (PET) and polyethene high-density (PE-HD) are used. Interestingly, poly(lactic acid) (PLA) is not found. Closures (caps) are responsible for 5 to 30% of the total packaging weight. Typical filling efficiencies are 20 to 40 g food product packaged in one gram of packaging material. For glass packagings, the values are 1.5 to 2 g food product packaged in one gram of packaging material. Therefore, plastic packaging results in an at least ten-times lower packaging use per unit of food, at single use packagings. With increasing product weights, we observe a tendency towards higher packaging efficiencies. By using paper/carton wrapping at cups, plastic use is reduced for the whole packaging.

Development of an inter-confirmatory plastic characterization system using spectroscopic techniques for waste management

Ever-accumulating amounts of plastic waste raises alarming concern over environmental and public health. A practical solution for addressing this threat is recycling, and the success of an industry-oriented plastic recycling system relies greatly on the accuracy of the waste sorting technique adapted. We propose a multi-modal spectroscopic sensor which combines laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy in a single optical platform for characterizing plastics based on elemental and molecular information to assist the plastic identification-sorting process in recycling industries. The unique geometry of the system makes it compact and cost-effective for dual spectroscopy. The performance of the system in classifying industrially important plastic classes counting PP, PC, PLA, Nylon-1 1, and PMMA is evaluated, followed by the application of the same in real-world plastics comprising PET, HDPE, and PP in different chemical-physical conditions where the system consumes less than 30 ms for acquiring LIBS-Raman signals. The evaluation of the system in characterizing commuting samples shows promising results to be applied in industrial conditions in future. The study on effect of physical-chemical conditions of plastic wastes in characterizing them using the system shows the necessity for combining multiple techniques together. The proposal is not to determine the paramount methodology to characterize and sort plastics, but to demonstrate the advantages of dual-spectroscopy sensors in such applications. The outcomes of the study suggest that the system developed herein has the potential of emerging as an industrial-level plastic waste sorting sensor.