Autor(es): Diana Ita Nagy, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
Comprehensive methods for estimating mismanaged waste accumulation in the environment are limited, especially in the Global South, and new technologies are urgently needed. Here, we applied the Azure system, a physical floating barrier designed to retain and extract river floating waste while providing observational data of mismanaged waste, comparing results with a modeling tool that uses material flow analysis toprovide estimates of mismanaged waste, incorporating environmental and socioeconomic factors. The Azure system was installed at the Portoviejo River (Ecuador), and anthropogenic litter was removed, extracted, weighed, and classified. Approximately 13.8 tonnes (t) of litter were collected over 2 years of sampling, of which 87% were plastic bags containing domestic waste. About 45% of the total waste collected, that is, 6.2 t, was estimated to be plastic waste. In contrast, modeled mismanaged plastic waste estimates for the Portoviejo River varied between 148 and 1858 t per year, at least two orders of magnitude higher than field data. These results highlight the discrepancy that can occur between observational data and waste estimates.The factors that contribute to this are discussed here to help understand riverine waste sources and transport to the ocean.The results emphasize the need for a better understanding of socioeconomic and environmental aspects in the Global South to help the development of better modeling tools. Our findings of domestic deposition as a major source of riverine contamination in the Portoviejo watershed emphasize the importance of waste management for tackling river contamination. Effective monitoring tools, such as the Azure system, could help improve this.
Ir al enlaceAutor(es): Ian Vázquez Rowe
This report evaluates methods from Life Cycle Assessment (LCA) and fisheries science concerning the impacts of fishing on exploited stocks and the seabed, using three case studies to assess feasibility and make recommendations for the European Footprint (EF) development. For fish stock exploitation, both fields offer suitable methods, but challenges remain in integrating them with the 16 EF indicators. The LCA method adopts an "Intrinsic biodiversity" approach, considering each kilogram removed as impactful. In contrast, the fisheries approach uses an "instrumental approach," viewing fishing as sustainable if stocks are not overfished, aligning removals with biomass renewal. The report highlights integration challenges and suggests consulting stakeholders to choose the best-suited approach for EF applications. Regarding seabed impacts, the LCA method lacks maturity and global data support for EF use, but this may improve. Meanwhile, the semi-quantitative approach from fisheries science is recommended for inclusion as a new characterization factor, having been successfully applied to the case studies and suitable for all EU seafood products. Lastly, a qualitative approach combining letter grades for stock depletion and seabed impact is discussed as a contingency, intended as a third and second option, respectively, for resource and seabed evaluations.
Ir al enlaceAutor(es): Ian Vázquez Rowe
Life cycle assessment (LCA) is the method most frequently used to systematically assess the environmental impacts of products and services over their entire life cycle. Several environmental impacts, such as global warming or ozone depletion, are covered. Life cycle assessments do not yet allow, however, for considering the consequences of plastic waste leaking into the environment. Thus, plastic products such as PET bottles might appear beneficial (having, for example, a lower carbon footprint than alternatives such as glass bottles) although they contribute to potentially harmful effects if released into the environment. In addition, the absence of an impact assessment method addressing plastic emissions limits the possibility of analyzing the trade-offs between impact categories. In order to provide an overview of the state of the art of plastic emissions in LCA, the chapter begins with an overview of the LCA methodology in general. There follows a description of the potential impact pathways of plastic emissions using a framework developed by the International Working Group MarILCA on Marine Impacts in Life Cycle Assessment. Within the framework, relevant existing impact categories are discussed, and new ones are proposed. The following section describes accounting methods for plastic emissions and ways of defining plastic flows in life cycle inventory (LCI). The already developed approaches addressing plastic emissions in life cycle impact assessment (LCIA) are then described in relation to the framework and, in addition, examples of applications (case studies) are presented. Finally, future research needs are discussed.
Ir al enlaceAutor(es): Luis Izquierdo Horna, Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe
Accurately forecasting municipal solid waste (MSW) generation is essential for designing efficient waste management systems and promoting sustainable urban development. As cities expand and consumption patterns shift, reliable data-driven approaches are increasingly necessary to address the complexities of MSW generation. This study applied the random forest (RF) algorithm, a machine learning technique, to predict MSW generation at the household level. RF was selected for its capacity to handle non-linear relationships, imbalanced datasets, and outliers. The analysis focused on data from 2019, avoiding distortions associated with the COVID-19 pandemic. The model integrated per capita MSW data with household fuel consumption indicators (i.e., natural gas, electricity, and liquefied petroleum gas) and demographic variables such as age, education level, and monthly expenditure. The case study focused on the city of Lima, Peru, using 80 % of the data for training and 20 % for testing, with hyperparameters optimized via 5-fold cross-validation. The final model explained 55 % of the variance in MSW generation (R2 = 0.55). This result reflects the model’s ability to capture significant drivers of variability, although it leaves room for refinement due to factors not included in the analysis, such as cultural practices or seasonality. Among the predictors, household monthly expenditure on cooking fuels emerged as the most influential variable, reinforcing the connection between resource consumption and waste generation. These findings highlight the potential of integrating socioeconomic indicators into predictive models to enhance their reliability. By improving forecasting capabilities, this study supports targeted policies for urban waste management and sustainable resource use.
Ir al enlaceAutor(es): Alejandro Deville del Águila, Ian Vázquez Rowe, Angel Avadí, Ramzy Kahhat Abedrabbo
The anchoveta (Engraulis ringens) fishery in Peru, which is almost entirely devoted to the production of fishmeal and fish oil, is one of the largest fisheries in the world. It is volatile in terms of fishing stock availability, and the fishmeal industry has been subject to technological changes to upgrade its efficiency and reduce costs to maintain its competitiveness. The objective of this study is to apply the Life Cycle Assessment methodology to the production and exportation of fishmeal and fish oil products related to a relevant producer in Peru, representing 10 % of national production. A set of 169 vessels targeting E. ringens were inventoried, 88 % of which are owned by third parties, and four factories belonging to the company were assessed for the years 2019 and 2021. Ecoinvent was the selected database to support the life cycle inventory, and ReCiPe 2016 and IPCC 2021 were the methods applied to compute the environmental impacts. The results show that fuel combustion in fishmeal and fish oil production was the dominating activity in most of the impact categories analyzed. In terms of greenhouse gas emissions, it was found that, on average, approximately 320 kg CO2eq and 4430 kg CO2eq are emitted due to the production of 1 t of fishmeal and 1 t of fish oil, respectively, when an energy allocation is followed. The fishery accounted for ca. 45 % of greenhouse gas emissions and dominated most of the impact categories, showing greater influence of the fishing stage than in previous studies. The reasons behind are linked to the combined influence of improvements in the energy matrix of the plants, by prioritizing natural gas over diesel and residual fuel oils, and a slightly higher fuel use intensity of the fishing fleet. E. ringens quality was found to be an important parameter, as low protein or fat yields translate into substantially higher impacts. Finally, although Peruvian fishmeal and fish oil remain as one of the lowest environmental footprint products among animal feed, future work is needed to understand the effects that climate change and El Niño-Southern Oscillation events have on this industry.
Ir al enlaceAutor(es): Alejandro Deville del Águila, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
Microplastic (MP) pollution has been largely documented in aquaculture systems, farmed animals, fishmeal, and feed, as well as in humans due to ingestion from food, including seafood, although a skew remains with fisheries and supply chains more commonly assessed for MP pollution in the Global North. In this sense, the main objective of this short communication is to explore how Peru, the biggest fishmeal, and fish oil (FMFO) producer worldwide, performs in terms of plastic pollution in fisheries and derived seafood products. For this, the available scientific literature has been analyzed. Our analysis suggests that studies in Peru are scarce, and more research must be undergone to evaluate the full extent of plastic pollution in its seafood supply chains. The literature analyzed suggests that pelagic species are more vulnerable to MP exposure and ingestion, and that a gradient in terms of closeness to the coast and depth of the fishery may be determining the level of occurrence and abundance of MPs in Peruvian fisheries. Furthermore, the combination of lack of measures for controlling plastic leakage to the ocean in Peru, with the closeness to the coast of most fishing grounds makes the Peruvian fishing industry highly vulnerable to plastic pollution. In this sense, as the Peruvian FMFO industry overwhelmingly targets anchoveta (Engraulis ringens), a pelagic fish, MP pollution of FMFO products must be monitored, as occurrence could lead to an introduction of MPs in aquaculture products worldwide and subsequent human consumption.
Ir al enlaceAutor(es): André Torre, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
Wastewater treatment plants (WWTPs) are not specifically designed to tackle microplastics (MPs), leaving them in aquatic ecosystems. The novelty of our study is a critical review of the effectiveness of conventional activated sludge (CAS), membrane bioreactors (MBRs), and activated granular sludge (AGS) in managing MPs within WWTPs. We bridge a gap in scientific literature by assessing MP removal and resilience to MPs. Our scope extends beyond MPs management, evaluating these technologies against environmental, economic, and social criteria. Findings show that MBR outperforms CAS and AGS in MP removal but faces challenges with smaller MPs due to fouling and secondary pollution. AGS shows similar removal rates to CAS but often superior resilience to MPs, given its higher decontamination capabilities. Environmentally, AGS may better reduce indirect greenhouse gas (GHG) emissions due to lower energy and chemical demands. Moreover, AGS exhibits higher resource recovery potential (e.g., biopolymers, phosphates). Socially, MBR excels in pathogen removal, reducing waterborne disease risks. Economically, AGS is the most cost-effective technology regarding both operational and capital expenditures. However, MPs can impact these criteria by reducing nutrient removal efficiency and increasing both direct and indirect GHGs. MPs create “plastisphere” habitats, reducing pathogen removal and compromising water safety. Moreover, MPs increase energy and chemical use, especially in MBR systems due to fouling concerns.
Ir al enlaceAutor(es): Joan Sánchez Matos, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
Water scarcity is a critical environmental challenge which will be exacerbated by the effects of climate change and increased human demand. Hence, more precise and realistic methods of quantifying this impact are necessary. In this sense, the present study proposes updated water scarcity characterization factors (CFs) for watersheds in Peru using the AWARE method. The novelty is linked to the consideration of present and future conditions, as well as quasi-cyclical climatic events such as El Niño.
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