Brazilian recycling potential: Energy consumption and Green House Gases reduction

Colling, Angéli Viviani; Oliveira, Luciano Basto; Reis, M.M.; Cruz, Nicolas; Hunt, Julian David

doi:10.1016/j.rser.2015.12.233

Cited by 29 publications

(19 citation statements)

References 2 publications

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“…By this initiative, countries compromise to establish their own targets for the reduction of greenhouse gases which implies indirectly the reduction of the consumption of non-biodegradable materials. This is because the decrease provides a smaller amount of material sent to landfills, which reduces the production of greenhouse gases [1–5]. Another factor that contributes to it is the increasing use of biodegradable materials due to the results of research related to discovery and production of new materials [1, 6–11], as well as the use of alternative non-toxic and biodegradable source of energy as biodiesel [12–15].…”

Section: Introductionmentioning

confidence: 99%

Classification of biodegradable materials using QSAR modelling with uncertainty estimation

Rocha

Sheen

2016

SAR and QSAR in Environmental Research

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The ability to determine the biodegradability of chemicals without resorting to expensive tests is ecologically and economically desirable. Models based on quantitative structure-activity relations (QSAR) provide some promise in this direction. However, QSAR models in the literature rarely provide uncertainty estimates in more detail than aggregated statistics such as the sensitivity and specificity of the model’s predictions. Almost never is there a means of assessing the uncertainty in an individual prediction. Without an uncertainty estimate, it is impossible to assess the trustworthiness of any particular prediction, which leaves the model with a low utility for regulatory purposes. In the present work, a QSAR model with uncertainty estimates is used to predict biodegradability for a set of substances from a publicly available data set. Separation was performed using a partial least squares discriminant analysis model, and the uncertainty was estimated using bootstrapping. The uncertainty prediction allows for confidence intervals to be assigned to any of the model’s predictions, allowing for a more complete assessment of the model that would be possible through a traditional statistical analysis. The results presented here are broadly applicable to other areas of modeling as well, because the calculation of the uncertainty will clearly demonstrate where additional tests are needed.

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Section: Introductionmentioning

confidence: 99%

Classification of biodegradable materials using QSAR modelling with uncertainty estimation

Rocha

Sheen

2016

SAR and QSAR in Environmental Research

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“…This figure increases if avoided emissions due to transport and non-energy processes are included. However, the methodology applied in this paper does not take into consideration the calculation for the generation of leached, as it is limited in the results obtained [81]. A second limit derives from the fact that the methodology used does not consider fuel consumption for the production of recycled materials.…”

Section: Discussionmentioning

confidence: 99%

Environmental and Socioeconomic Impacts of Urban Waste Recycling as Part of Circular Economy. The Case of Cuenca (Ecuador)

2020

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Urban mining by recyclers represents a positive environmental impact as well as being part of the waste management chain. This paper analyzes the contribution of waste pickers in the city of Cuenca in Ecuador and the conditions of their activity. This research has a two-fold objective. First, it calculates the reduction of greenhouse gas emissions resulting from the substitution of virgin raw material in the production process by using recycled urban waste. The second objective is to conduct a socioeconomic analysis of the workers involved in the urban waste sector. Cuenca (Ecuador) is the main city used for this case study, thanks to the accessibility of a rich database built from the survey conducted by the NGO Alliance for Development. The information contained in this survey facilitates the identification of potential consumers of the waste industry. This study uses Clean Development Mechanism methodology. Finally, this work proposes a theoretical model for solid waste management, applied to the city, following the principles of the circular economy.

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“…While less than 30% of generated plastic waste is recycled in Europe (PlasticsEurope 2016) and no more than 10% in the USA (US Environmental Protection Agency 2016), the recycling rates tend to be even lower in developing countries with incipient waste management systems, such as Brazil (Colling et al 2016;Palombini et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Occurrence and recovery of small-sized plastic debris from a Brazilian beach: characterization, recycling, and mechanical analysis

Palombini

Demori

Cidade

et al. 2018

Environ Sci Pollut Res

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Small-sized plastic debris are an increasing global concern, particularly in environmental protected areas. Consequently, tourism-based economy of poor coastal regions is also impaired. Nevertheless, little interest has been shown about recycling approaches of such materials, mostly because of the natural degradation of polymers on these conditions. This research presents the report of the occurrence of plastic debris nearby Lençóis Maranhenses National Park, on the northeast Brazilian coast, aiming to provide a feasible method for recycling. We collected more than 80 samples from the sediment and classified them via FT-IR. Degraded polypropylene samples were selected for blending with virgin material using different concentration rates, and were mechanically tested. Tensile testing results suggest that 5% recycled material concentration mixture has suitable mechanical properties on the elastic regime for applications on new parts. Our findings show that particular interest should be addressed on the recovery of commodity plastic debris from environmental protected areas.

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Brazilian recycling potential: Energy consumption and Green House Gases reduction

Cited by 29 publications

References 2 publications

Classification of biodegradable materials using QSAR modelling with uncertainty estimation

Classification of biodegradable materials using QSAR modelling with uncertainty estimation

Environmental and Socioeconomic Impacts of Urban Waste Recycling as Part of Circular Economy. The Case of Cuenca (Ecuador)

Occurrence and recovery of small-sized plastic debris from a Brazilian beach: characterization, recycling, and mechanical analysis

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