Autor(es): Rubén Manrique, Alejandro Deville del Águila, Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe
Purpose: Biodiversity impacts of the Peruvian fisheries, strongly influenced by El Niño-Southern Oscillation (ENSO), are not fully covered by current life cycle impact assessment (LCIA) models. While the recently developed Fisheries Impact Pathway (FIP) accounts for the impacts of marine biotic resource depletion, key methodological challenges, such as temporality, critical for impact assessment in dynamic fisheries, remain unattended. In the current study, we aim to develop characterization factors (CFs) for 10 relevant Peruvian fishing stocks, including Peruvian anchoveta, using an enhanced FIP framework. Methods: The methodological framework includes 1) optimization of CMSY++ performance using an exhaustive statistical analysis, to provide reliable estimates for subsequent CF calculations; 2) calculation of CF time series under an Exclusive Economic Zone (EEZ) approach; and, 3) statistical evaluation of enhanced CFs comprising typical uncertainty and sensitivity analyses, along with other tests addressing ecological soundness and stock management; and, 4) application of CFs in case studies to quantify biodiversity impacts from fishing for direct and indirect human consumption. Results and discussion: Enhanced CFs deviate up to 4 orders of magnitude from previously reported values, usually showing lower values. These CFs also exhibit weak-moderate statistical correlation with typical ENSO indices, with sea level anomalies showing the strongest relationship. Furthermore, case studies framed in the Peruvian EEZ confirm the relevance of the enhanced CFs, unveiling significant differences in fishing impacts of stocks destined to direct human consumption during years with El Niño and La Niña events, and additional LCIA impacts, ranging from 0.1% to 61% in fishmeal and fish oil production among plants of a major producer, during years 2019 and 2021. Together, these findings suggest that addressing temporality is critical to refine LCIA results, especially in systems with highly dynamic parameters. Conclusions and recommendations: The enhanced CF time series more accurately represents stock population dynamics, under fluctuating climatic stressors and management regimes, than the original FIP method. Thus, our method responds to the call of international LCA guidelines for regionalized and temporally explicit impact assessment. We recommend using these CFs to assess biotic resource depletion in Peruvian seafood and aquaculture systems, and extending our methodology to other EEZs affected by similar ecosystem dynamics and fishing pressure.
Descargar publicación (7,69 MB)Autor(es): Eizo Muñoz Sovero, Ramzy Kahhat Abedrabbo, Alejandro Deville del Águila, Diana Ita Nagy, Ian Vázquez Rowe y David Gonzales
Illegal, unreported, and unregulated (IUU) fishing activities have historically been difficult to detect due to a lack of adequate monitoring and surveillance technologies. In recent years, advances in computational capacity and the growing availability of fleet tracking datasets have enabled the development of algorithm-based tools for monitoring fishing activity. Additionally, satellite geolocation systems, such as Automatic Identification Systems (AIS) and Vessel Monitoring Systems (VMS), have been implemented across multiple fishing fleets worldwide, further enhancing surveillance capabilities. The current study proposes the combined use of AIS and VMS data with satellite imagery to detect and characterize IUU activities of foreign fishing vessels targeting the tuna fishery in the Peruvian Exclusive Economic Zone (EEZ) in the year 2022. Fishing effort was quantitatively characterized according to permit compliance considering three categories of IUU activities: fishing beyond the permit timeframe, inside a marine protected area (MPA), or without a valid permit. Out of a total sample of 61 vessels evaluated, 56 were detected fishing within the Peruvian EEZ, of which 47 operated within allowed permit lengths, 6 exceeded their authorized days within the EEZ, and 3 had no permit at all. However, of the 47 vessels complying with their permit timeframes, 16 engaged in IUU fishing within the Dorsal de Nasca MPA. These results revealed distinct behavioral patterns of fishing effort not only within the Peruvian EEZ, but also within the broader Eastern Pacific Ocean.
Ir al enlaceAutor(es): Alvaro Elorrieta y otros
The circular economy is increasingly recognised as a multidimensional paradigm that goes beyond reducing waste and recycling, encompassing systemic design, regenerative practices, socio-technical innovation, and equity considerations. This study examines Peru’s efforts to transition towards circularity as a representative emerging economy in Latin America, based on 15 semi-structured interviews with stakeholders from academia, policymaking, business, and non-governmental organisations. It provides new empirical insights by identifying context-specific drivers and barriers not previously reported in the literature. The analysis identifies barriers such as limited consumer awareness, weak enforcement of regulations, technological gaps, and financial constraints affecting especially micro, small, and medium enterprises. Drivers and strengths include international cooperation, biodiversity, ancestral knowledge, and emerging policies. The government, European agencies, and civil society emerge as central actors in this transition. Conceptually, the study offers a novel contribution by adapting Schlossberg’s transition theory, traditionally applied in psychology and education, to the field of sustainability. Findings emphasise the need to raise awareness, foster a cross-sectoral and decentralised regulatory framework with clear responsibilities, enforcement, and accountability mechanisms, promote targeted investments, and design policies that integrate informal sectors. This research contributes to both theory and practice: methodologically by extending transition theory to sustainability studies, and empirically by providing the first multi-stakeholder analysis of CE in Peru, offering insights for policymakers seeking to balance environmental and economic goals.
Ir al enlaceAutor(es): Alvaro Elorrieta y otros
A well-functioning circular economy (CE) integrates resilience across economic, environmental, and social dimensions. This study identifies key drivers and barriers to Brazil's CE transition through 20 semi-structured interviews with stakeholders. Major sociocultural barriers include inadequate education and limited CE awareness, while growing environmental consciousness and traditional reuse practices act as drivers. Policy barriers stem from the absence of dedicated CE regulations, though national sustainability efforts offer opportunities. Technological limitations arise from insufficient research, but efficiency-enhancing innovations and digital business models show promise. Economically, high transition costs hinder progress, whereas resource efficiency boosts competitiveness and job creation. Key priorities for advancing CE include raising public awareness, integrating CE into education, supporting waste pickers, developing decentralised regulations, improving waste management, fostering innovation hubs, and providing financial incentives for circular business models. Stakeholder engagement—particularly policymakers, civil society, and private enterprises—remains essential to accelerating CE adoption in Brazil.
Ir al enlaceAutor(es): Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe y David Baptista de Sousa
The marine ingredients (MIs) industry is essential to the aquaculture sector, mainly providing fishmeal and fish oil to support animal feed and human nutrition. The exponential growth of aquaculture and the heavy reliance on finite marine resources pose significant sustainability challenges and highlight the need for more comprehensive and regionally adapted metrics beyond current Life Cycle Assessment (LCA) indicators and nonconventional LCA metrics. In this systematic review, we analyzed 48 literature studies that focus on the sustainability of MIs using rigorous criteria for data quality and indicator relevance under the Prisma methodology. Our findings indicate that the studies that are mainly based on conducting an LCA provide valuable insights into environmental performance, but are hindered by inconsistent metrics, limited data availability, and a lack of integration of economic, nutritional, and ethical dimensions in the sustainability analysis. Such limitations can lead to underestimate critical issues such as biodiversity loss, overfishing, habitat degradation, or the impact of illegal fishing, while overemphasizing short-term efficiency measures, like feed conversion ratio, or environmental impacts such as global warming. Additionally, emerging novel proteins and alternative uses for fish-derived byproducts, ranging from direct human consumption to high-value applications (bioactive compounds, cosmetics, etc.) to lower value products (like biofertilizers), remain largely unexplored, given the absence of holistic and flexible assessment tools. Thus, the presence of unregulated contaminants (including additives, antibiotics and microplastics), are not yet adequately addressed in most MIs studies, despite some recent methodological advancements. This review proposes the adoption of novel metrics, the standardization of assessment methods and the integration of multi-criteria decision analysis for LCA practitioners to better capture the complex and multifaceted challenges of MIs production, covering the way for more robust and reliable sustainability assessments within the aquaculture industry.
Ir al enlaceAutor(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): 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.
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