Resources Conservation and Recycling最新文献

The aim of this work was to find the optimal resource-efficient treatment alternative for organic waste from the food industry. For that, four different treatment methods for thirteen feedstocks were studied: animal fodder production, incineration, biological treatment and biogas production. An optimization model was used to find which treatment alternative is the optimal from a variety of perspectives.

The studied systems were evaluated from three different evaluation perspectives: economy, energy and environment. The energy evaluation included two different electricity systems: coal condensing power and wind energy.

The results show that there is no single optimum feedstock treatment method taking all the perspectives studied into account. Instead, it is important to consider all different perspectives when evaluating the resource efficiency of the treatment method for a feedstock. However, both incineration and anaerobic digestion of the food waste can be considered as resource-efficient treatment options for the studied feedstocks.

The recently reported Solvent-Targeted Recovery And Precipitation (STRAP) strategy is used to deconstruct multilayer plastic packaging films into their constituent resins by selective polymer dissolution. To broaden the applicability of STRAP, we demonstrate the process with a flexible post-industrial printed multilayer plastic film used for food packaging. The material was a reverse printed film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), polyethylene terephthalate (PET), and polyurethane (PU)-based inks. Removal of all colors was observed with biomass-derived gamma-valerolactone (GVL) and the recovered polymers possessed comparable properties to the corresponding virgin resins. A technoeconomic analysis indicates that this STRAP process could be economically feasible at a processing capacity of 6,000 tons per year. Moreover, the production of plastic films with materials recovered by this STRAP process can have a lower climate change impact than the production of films from virgin polymers.

The rapid global adoption of solar photovoltaic (PV) modules created the issue of recycling and disposal at their end of life. Several PV modules installed in the late 1980s or early 1990s have reached the end of their 30-year useful life and are now being removed as PV trash. This enormous amount of PV trash acknowledges recycling as a crucial and significant area in the value chain of PV industries. Hence, this study uses an end-of-life perspective to discuss the life cycle evaluation of two market-dominant PV technologies— c-Si and CdTe. This method examines recycling and avoided burden due to recovered material independently in order to determine the overall environmental benefit. The study concludes that recycling glass, metals like copper and aluminium, and semiconductor material from both c-Si and CdTe PV modules has a lower environmental effect than mining, providing, and refining the same components from original sources.

Phosphorus is a key non-renewable element used in multiple economic activities, and notably for food production. It is therefore a critical material whose recovery is gaining interest. This work maps the annual phosphorus flows across Ontario's economic sectors through material flow analysis using open data sources. This information is used to identify potential opportunities for phosphorus recovery and recycling, all while performing an economic assessment to determine the feasibility of phosphorus recovery from different sectors. Up to 86% of phosphorus imports for food production could be covered by recycled phosphorus, with an average recovery cost of 49 CAD/kg of phosphorus. This cost is lower than the estimated economic losses caused by phosphorus releases into the environment, although it is significantly higher than the cost of fossil-based phosphorus products. However, phosphorus recovery costs vary widely for different waste streams, suggesting the need of exploring cooperative approaches for effective phosphorus recovery at regional scale.

This study considers the suitability of end-of-life cotton textiles as a precursor for activated carbon fibre (ACF) cloth for noise attenuation. The study presents a materials transformation and valorisation technique to increase circularity of waste textiles, which is supported by strong end markets and increasing demand.

Thermal and chemical parameters were modified to identify the preferable settings for maximising the surface area of the activated carbon fibre cloth. The surface area was tested using Brunauer-Emmett-Teller (BET) Analysis. The least amount of phosphoric acid (H₃PO₄) on the sample yielded the highest surface area when comparing textile to acid dosage ratios of 1-1, 1-2, 1-3 and 1-4. Varying the water content in the 1-1 ratio had little effect on the surface area but did affect the structure. The textile - acid - water ratio of 1-1-4 was preferable to 1-1-2, as more of the textile structure remained intact under the naked eye and under the Scanning Electron Microscopy (SEM). Samples transformed under a temperature of 850 °C had a higher surface area than samples transformed at 650 °C and 950 °C, which were 1900 m²/g, 1500 m²/g. and 1600 m²/g respectively.

To maximise noise attenuation, multi-layer activated carbon fibres were created by layering the textiles prior to chemical and thermal transformation processes. By increasing the scale of production, the surface area was reduced. However, the multi-layer ACF yielded promising results even with a modest surface area of approximately 1300 m²/g. The analysis showed that the ACFs were superior to broad spectrum acoustic foams for higher frequency sound desipite being one fifth of the corresponding thickness. The findings from this study are promising for applications requiring a very thin noise attenuating barrier. This advanced material could increase circularity of waste textiles in Australia and reduce the impact of noise pollution in urban environments.

Plastic waste management represents a global challenge in the framework of sustainable production and consumption of resources. One of the most critical issues in plastic recycling is polymer separation, necessary to obtain high-quality secondary raw material flow streams. The aim of this work was to build a classification strategy, based on pushbroom hyperspectral imaging, able to recognize the most common polymers found in mixed plastic waste to be applied at recycling plant scale. After exploring polymer spectral differences by principal component analysis, a hierarchical partial least squares-discriminant analysis, based on the acquired full spectra, and a hierarchical interval partial least squares-discriminant analysis, based on selected variables, were tested and their performances were evaluated and compared. High quality classification results were obtained in both cases, demonstrating that the developed multi-class models can be utilized in a flexible way for quality control and/or for on-line sorting actions in recycling plants.

The frequent deterioration of coastal fisheries has resulted in a need to nourish the world's rapidly expanding population, contributing to a substantial shift toward fishing in the mesopelagic zone. These areas contain a potentially huge amount of fish biomass. Considering that the global population will demand an increase of 60% in food production by 2050, it appears that exploiting the mesopelagic resources is simply a question of time. The present paper reviews the major risks and opportunities related to the exploitation of mesopelagic fisheries. Due to the significance of the uncertainties related to the stock of fish resources, environmental and biodiversity effects of the deep-sea fisheries, this inquiry advocates for the enhancement of sustainable small-sized deep-sea fishery practices on the one hand side and a global moratorium on large-scale mesopelagic fishing on the other hand. Deep seas could provide substantial resources for combating global food insecurity and facilitate a substantial improvement of the nutritional status in the regions plagued by a high incidence of infant mortality and disproportional poverty headcount ratios. For the sake of global and regional food and nutrition security, the exploitation of the biological resources of the mesopelagic zone is a legitimate target, whereby environmental sustainability is the major precondition for the rollout of these kinds of fishing activities.

Since 2013, the Chinese Government implemented “Clean Air Action” Phase I (2013–2017) and Phase II (2018–2020) consecutively to improve air quality. However, it remains unclear how these policies have impacted air quality since most studies merely focus on Phase I. In this study, we applied the Community Multiscale Air Quality (CMAQ) model to investigate variations of air quality in China during “Clean Air Action” Phases I and Phase II (2013–2020). Results show that PM_2.5 is significantly reduced (-40%) across China except in summer. O₃ concentration also decreases, but a 3% increase is found in the Beijing-Tianjin-Hebei (BTH) region. Emission changes play a dominant role in the reduction of PM_2.5 (over 95%). The contributions from meteorology and emissions to O₃ reduction are 46% and 54%, respectively. Our results suggest that a more effective emission abatement strategy should be formulated, aiming to control O₃ and PM_2.5 synergistically.

Recycling plastics can reduce waste generation and improve waste management, but the recycling industry needs both cost reduction and increased revenue to be economically viable. Recently, recycling plastic classification techniques with Artificial Intelligence have gained popularity, as they can avoid manual sorting, which is time-consuming and economically less profitable than automatidc processing. In this paper, we provide an economic framework for quality sorting control by classifying plastics based on the infrared spectrum of polymers and machine learning algorithms. In addition, the suggested framework offers a method for selecting the algorithm according to the polymer's income class and the highest economic advantages. Furthermore, our experiments probe that Fourier-transform infrared (FTIR) and near-infrared (NIR) spectroscopies combined with machine learning algorithms are suitable for plastic classification as four datasets and seven machine learning algorithms have been tested to classify Polyethylene (PE), Polypropylene (PP), Polyethylene terephthalate (PET), polystyrene (PS), and Polyvinyl chloride (PVC).

As sustainability and circularity are emerging as the new normal for business, manufacturers have attempted to apply recovery strategies such as reuse, remanufacturing, and recycling to product family design to generate higher profits and mitigate the environmental impact. Compared to single-product design, product family design involves developing sharing decisions in which components and operations are common across product variants. However, existing approaches have not clearly explained the multi-lifecycle effects of sharing decisions. This paper proposes an evaluation model that quantifies the multi-lifecycle economic profit and environmental impact of a product family design. A bi-objective optimization model with economic and environmental objectives is developed to assess the effects of sharing over multiple lifecycles. The evaluation results provide a broader understanding of the multi-lifecycle effect of component and operation sharing and the trade-off between economic profit and environmental impact. This study considers a smartphone family design case to validate the proposed model.