Search Results (36)

Plastic pollution in freshwater ecosystems is an increasing environmental concern, prompting the search for biodegradable polymer (BP) alternatives. However, their degradation in natural aquatic environments remains poorly investigated and understood. This four-month in situ study compared the degradation in a lentic freshwater ecosystem of two compostable items, Mater-Bi^® shopping bag and disposable dish, with their respective pure polymer matrices, poly(butylene adipate-co-terephthalate) (PBAT) and polylactic acid (PLA). Additionally, biodegradable poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and oil-based polypropylene (PP) were also tested. Changes in morphology, chemical composition and thermal and mechanical properties, as well as microbial colonization, were analyzed over time. A validated cleaning protocol was employed to ensure accurate surface analysis. Results showed detectable but limited degradation of pure polymers and their matrices in commercial products after 120 days of immersion with variations observed among polymer materials. Compostable materials exhibited significant leaching of fillers (starch, inorganic particles), leading to morphological changes and fragmentation. PHBV showed the fastest degradation among tested polyesters. PP exhibited only minor surface changes. Microbial colonization varied with polymer structure and degradability, but long-term degradation was limited by polymer properties and the gradual development of the plastisphere. This study highlights that standard laboratory tests may overestimate the environmental degradability of BPs and emphasizes the importance of in situ assessments, careful cleaning procedures and property characterizations to accurately assess polymer degradation in freshwater systems. Full article

Single-use plastics (SUPs) are deeply embedded in everyday consumption in rapidly developing Asian cities, yet their widespread use contributes to marine debris, microplastic pollution, and health risks. This study aimed to inform evidence-based policymaking to mitigate marine plastic pollution in the ASEAN+3 region. Stratified random sampling surveys (n = 1492) were conducted both face to face and online across five representative cities between September 2022 and February 2023. We quantified and compared the consumption and disposal patterns across nine SUP categories, assessed demographic influences, evaluated the impact of COVID-19, and derived insights for targeted policy interventions. Non-parametric tests were used to evaluate the differences. The results reveal significant inter-city variation: Shanghai and Harbin reported high overall SUP use despite a lower consumption of plastic shopping bags; Hanoi and Depok showed lower overall use but distinct preferences for plastic shopping bags and party cups; and Phnom Penh had the highest consumption of plastic shopping bags, bottles, and straws. Plastic shopping bags were the most used item in all cities (18–34 bags per week), with no significant differences between urban and rural areas, ages, or genders. In contrast, urban residents reported a higher use of plastic takeout containers, cutlery, coffee cups, and party cups. The COVID-19 pandemic notably reshaped SUP consumption patterns. Additionally, over half of SUPs were disposed of without proper separation. These findings underscore the need for flexible, phased, and context-specific interventions to support a resilient circular economy. Full article

This research examined the persuasive impact of social norms and financial incentive messaging for encouraging reusable bag use. In an online experiment with a nationally representative sample from the U.S. (n = 753), participants were randomly exposed to static or dynamic descriptive/injunctive norms, discounts/surcharges, combinations, or a control message. Intentions to bring reusable bags when grocery shopping, along with other key demographic and psychological variables, were assessed. ANCOVA results demonstrate the main effects of the messages. Planned contrasts revealed that injunctive norms elicited higher intentions than descriptive norms. Dynamic descriptive norms led to stronger intentions compared to static descriptive norms, with no difference shown between the two injunctive norm conditions. Notably, combining injunctive norms with either incentive boosted intentions beyond standalone messaging, supporting motivational complementarity. Norms overall outperformed incentives, but integrating social and economic appeals shows promise. The predicted superiority of experimental messages in promoting intentions, when compared to a generic pro-environmental appeal (control), was not supported. The findings advance an integrated behavior change approach highlighting normative information and incentives, shedding light on optimal messaging strategies amid pro-environmental interventions. Full article

This study aimed to compare the environmental performance of plastic bags made of three different polymers, considering two product functions: carrying goods and packing municipal solid waste. The three polymers studied were HDPE, LDPE, and thermoplastic starch (TPS). Life cycle assessment and emergy accounting were used to evaluate the environmental performance of each scenario in analysis. To develop this research, eight scenarios were created to represent the customs of use and consumption in the Brazilian population. The LCA results showed that, in general, the scenarios with HDPE plastic bags presented the best environmental performances, while those with TPS presented the worst. The processes that contributed most to these results, representing 70% or more of the environmental impact in each impact category, are related to the use of raw materials, electricity, and water for the manufacture of plastic bags and the treatment in landfills. In other words, the fact that TPS has a mass around six times greater than that of HDPE and two times greater than that of LDPE ends up leaving this type of polymer with the worst environmental performance. In the comparative analysis of scenarios for the same polymer, scenarios that involve the use and reuse of plastic bags present the lowest potential environmental impacts. In contrast, those related to the use and disposal in landfills present the highest possible environmental impacts. The results of emergy accounting showed that the HDPE scenarios had the lowest total emergy flow, ranging from 1.77 × 10¹³ seJ to 2.40 × 10¹³ seJ. In contrast, the LDPE scenarios had the highest total emergy flow, ranging from 1.15 × 10¹⁴ to 1.21 × 10¹⁴ seJ. Although LDPE had the highest total emergy flow values, these results are similar to those obtained by the fossil resource scarcity impact category, which focuses on resource consumption analysis. Thus, through a real approach to the use of plastic bags and solid waste management in the Brazilian context, this study brings essential insights to direct public policies related to the consumption of plastic bags. Full article

Addressing climate change necessitates reducing carbon emissions, with green behavior adoption being crucial. This study examines how green consumption awareness (GCA) and carbon emission disclosures influence consumer shopping channel choices, offering a practical approach to converting awareness into actionable behavior. Using stated preference (SP) data, we investigate the impact of green awareness and information disclosure on consumers’ choices between online and offline shopping channels. The key findings include the following: (1) GCA affects shopping channel choices in certain scenarios, though not always significantly. (2) Detailed carbon information disclosure steers consumers towards lower-emission channels, especially when specific carbon data are provided. (3) The type of goods significantly influences shopping channel decisions, serving as a variable across scenarios. (4) Effective scenarios, such as a 3 km shopping trip for categories like tissue and trash bags, where the difference in channel choice under varying levels of information disclosure is statistically significant, have been identified. These insights inform recommendations for information disclosure strategies that not only enhance GCA but also drive behavioral change, thereby fostering environmentally friendly consumption behaviors that contribute to a reduction in consumers’ carbon footprint. Full article

Bans on single-use plastic shopping bags (SUPBs) are a popular policy to tackle plastic pollution. However, their success has been evaluated solely based on reduced SUPBs consumption, ignoring the impacts of substitutes. This article addresses this gap by analyzing the Chilean plastic bag ban law. Results show a reduction of ~249 kilotons of SUPBs consumed and a change in the materiality of shopping bags (mainly toward paper), but also an increase of more than 50% of bin liners after the enactment of the ban. Despite some undesired effects, an improvement in the environmental performance of the bag market is obtained in fifteen of the eighteen categories studied. The environmental impacts are on average 38% lower than in the counterfactual scenario. This suggests that the law is being effective in protecting the environment. The strictness of the ban and its rapid enforcement were positive aspects of its design, but ignoring the end-of-life of the bags could be limiting its impact. To reduce the environmental impact of substitutes, it is recommended to create design guidelines for shopping bags and bin liners. Full article

In recent years, online shopping has surged in popularity, with customer reviews becoming a crucial aspect of the decision-making process. Reviews not only help potential customers make informed choices, but also provide businesses with valuable feedback and build trust. In this study, we conducted a thorough analysis of the Amazon reviews dataset, which includes several product categories. Our primary objective was to accurately classify sentiments using natural language processing, machine learning, ensemble learning, and deep learning techniques. Our research workflow encompassed several crucial steps. We explore data collection procedures; preprocessing steps, including normalization and tokenization; and feature extraction, utilizing the Bag-of-Words and TF–IDF methods. We conducted experiments employing a variety of machine learning algorithms, including Multinomial Naive Bayes, Random Forest, Decision Tree, and Logistic Regression. Additionally, we harnessed Bagging as an ensemble learning technique. Furthermore, we explored deep learning-based algorithms, such as CNNs, Bidirectional LSTM, and transformer-based models, like XLNet and BERT. Our comprehensive evaluations, utilizing metrics such as accuracy, precision, recall, and F1 score, revealed that the BERT algorithm outperformed others, achieving an impressive accuracy rate of 89%. This research provides valuable insights into the sentiment analysis of Amazon reviews, aiding both consumers and businesses in making informed decisions and enhancing product and service quality. Full article

Material flow analysis of plastics has attracted considerable attention for achieving sustainable production and consumption. However, the direct weights of each plastic have been analyzed alone, not considering the amount of natural resources as inputs for plastic production. Therefore, we analyzed the cradle-to-gate resource intensity of 21 types of plastics in terms of mining activity, using the total material requirement under the life cycle concept. It was found that the resource use for plastic production differs by up to approximately 10 times depending on the plastic type. By applying these findings to the material flow analysis of some countries and regions, we found that the quantity of natural resources was more than 20 times the original weight attributed to plastic production. By comparing resource use with greenhouse gas emissions, plastics with higher greenhouse gas emissions were found to have higher resource use, indicating a positive correlation, whereas the opposite trend was also found for some plastics. Considering plastic alternatives, we found that the quantity of natural resources in plastic-based shopping bags is nearly equivalent to that in paper-based bags, whereas that in plastic-based straws is greater than that in paper-based bags. Focusing only on the direct weight of plastic may mislead the decision-making process. Full article

The present study aims to explore the degradation process of compostable, starch-based (i.e., Mater-Bi^®) shopping bags in the marine environment using isotope ratio mass spectrometry and Fourier-transform infrared spectroscopy (FTIR). The mixing model applied to the isotopic data suggested that the compostable shopping bags had a mixed composition with a higher percentage of polyesters (61% to 72%). Changes in the isotopic composition over a 73-day period of marine water immersion showed a decrease in the corn starch constituent (of 14% to 13%), with a similar rate in both types of bags in accordance with the evidence derived from the infrared spectra. The time required for complete degradation of the starch fraction was estimated by an isotopic approach from 124 to 180 days, following zero-order kinetics. The coupled application of these two analytical methodologies promises to (i) show complementary evidence regarding the time-course degradability of different polymers via FTIR changes, and (ii) infer potential degradation mechanisms via carbon isotope analyzes. We encourage the use of this information to support advancements in the development of more sustainable-by-design plastic materials. Full article

Microbial surface contamination of the cooked ham sliced by shop assistants has an influence on its potential secondary shelf-life. Active packaging may be the solution. The first goal of the work was to obtain coatings based on Formitopsis betulina and Uncaria tomentosa extracts (separately), with the addition of nanoparticles of ZnO (as a synergetic agent to increase plant extracts’ antimicrobial effectiveness), that could be active against selected bacterial strains. Another aim of the work was to determine the influence of obtained active layers on microbial purity and texture of the samples. The results of the study demonstrated that the layers containing F. betulina or U. tomentosa extracts with the addition of ZnO nanoparticles inhibited Staphylococcus aureus, Bacillus atrophaeus, and Escherichia coli growth completely and decreased the number of Pseudomonas syringae cells. Analyzing microbial purity of sliced cooked ham portions after storage, it was observed that the active packaging based on U. tomentosa extracts had a greater influence on the total count than the coatings containing F. betulina extracts and that both active packaging materials affected the microbial purity of the cooked ham. Analyzing the textural parameter changes after 48 h of storage, a decrease in the gumminess, chewiness and cohesiveness values was noted, but only for the ham portions stored in bags covered with the coating based on U. tomentosa. The effectiveness of the active packaging on textural parameters after 96 h of storage was not noticed. Full article

Plastic shopping bags are often discarded as litter and can be carried away from roadsides and become tangled on cotton plants in farm fields. This rubbish plastic can end up in the cotton at the gin if not removed before harvest. These bags may not only cause problems in the ginning process but might also become embedded in cotton fibers, reducing the quality and marketable value. Therefore, detecting, locating, and removing the bags before the cotton is harvested is required. Manually detecting and locating these bags in cotton fields is a tedious, time-consuming, and costly process. To solve this, this paper shows the application of YOLOv5 to detect white and brown colored plastic bags tangled at three different heights in cotton plants (bottom, middle, top) using Unmanned Aircraft Systems (UAS)-acquired Red, Green, Blue (RGB) images. It was found that an average white and brown bag could be detected at 92.35% and 77.87% accuracies and a mean average precision (mAP) of 87.68%. Similarly, the trained YOLOv5 model, on average, could detect 94.25% of the top, 49.58% of the middle, and only 5% of the bottom bags. It was also found that both the color of the bags (p < 0.001) and their height on cotton plants (p < 0.0001) had a significant effect on detection accuracy. The findings reported in this paper can help in the autonomous detection of plastic contaminants in cotton fields and potentially speed up the mitigation efforts, thereby reducing the amount of contaminants in cotton gins. Full article

Machine learning frameworks categorizing customer reviews on online products have significantly improved sales and product quality for major manufacturers. Manually scrutinizing extensive customer reviews is imprecise and time-consuming. Current product research techniques rely on text mining, neglecting audio, and image components, resulting in less productive outcomes for researchers and developers. AI-based machine learning frameworks that consider social media and online buyer reviews are essential for accurate recommendations in online e-commerce shops. This research paper proposes a novel machine-learning-based framework for categorizing customer reviews that uses a bag-of-features approach for feature extraction and a hybrid DNN framework for robust classification. We assess the performance of our machine learning framework using AliExpress and Amazon e-commerce product review data provided by customers, and we have achieved a classification accuracy of 91.5% with only 8.46% fallout. Moreover, when compared with state-of-the-art models, our proposed model shows superior performance in terms of sensitivity, specificity, precision, fallout, and accuracy. Full article

The effect of 96 h exposure of the goldfish Carassius auratus to two different types of bioplastic particles, originating from commercial shopping bag (Bag, ~5 mm) and polylactic acid-based (PLA) cup (Cup, ≤5 mm), and petroleum-based polyamide particles (PA, 0–180 µm) was studied. All particles were studied as virgin and after simulated UV-degradation (at concentration 30 mg L⁻¹). The experiments were conducted according to OECD 203 test guidelines. The toxicity endpoint evaluated in fish brain and gills was lipid peroxidation (LPO) quantified as nmol thiobarbituric acid reactive substances (TBARs) mg⁻¹ protein. The results indicated that indicatively compostable PLA bioplastic Cup induced significant LPO in the brain and/or gills of the goldfish, in contrast to the particles from Bag and PA (in the brain, Cup > Bag > PA; in the gills, Cup > Bag). The UV-degradation of the particles of all studied types had no significant effect on the LPO level compared to virgin particles. While the increase of LPO in fish gills and brain upon exposure to PLA-plastic particles can be transitory in the long-term perspective, our results point to the necessity of a thorough investigation of the hazard of bioplastics at different state of environmental degradation/weathering. Full article

With the rapid growth of online grocery shopping in South Korea, e-grocery retailers have faced intense competition. Consequently, they attempt to differentiate themselves by offering diversified delivery services, such as providing early morning delivery services or eco-friendly packaging. The purpose of this paper is to analyze consumer preferences with regards to delivery services with different delivery times and packaging types targeting South Korea’s online grocery markets. Specifically, six delivery types consisting of combinations of two delivery time options (dawn, daytime) and three packaging types (paper box, market cooler bag, personal icebox) are examined. A survey was conducted in July 2020 with 218 consumers who regularly buy fresh food online. The collected data were analyzed by means of a conjoint analysis and ANOVA. The present study finds that customers most strongly prefer dawn delivery using a personal icebox, followed by dawn delivery using a market cooler bag, with daytime delivery using a paper box being the least preferable. Furthermore, consumers value the packaging type more than the delivery time when selecting a delivery service. Lastly, the preferences of consumers regarding delivery service types differ according to their characteristics. This study is expected to contribute to the establishment of a delivery strategy for online grocery companies. Full article

We aimed to understand how to promote innovative technology in the sustainable fashion market. The case study was the advertisement of a feminine bag with a chain coated using a new technology. We invited 550 women to read an Instagram post. In the control condition, the post only described the new technology. In the informational condition, the post emphasized the resistance and durability of the bag. In the transformational condition, the post emphasized the innovativeness and exclusivity of the bag. In the sustainability condition, the post emphasized the low environmental impact of its production. Results showed that the sustainability advertisement was the most persuasive in terms of consumers’ involvement, systematic processing, and intention to buy the bag. In addition, reference to the functional benefits was an effective strategy to promote purchasing intention when consumers were interested in novelty and high quality, and when engaged in shopping for fun and enjoyment. Full article