Author(s): Alvaro Elorrieta, Joan Sanchez Matos, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
(Español) Avocado production in Peru takes place in different biomes and under different agricultural systems (e.g., conventional, organic, or agroforestry). Therefore, it is important to understand differences in the environmental profile of avocado production within the diversity of these cultivation systems. Hence, the main objective of the study was to conduct a cradle-to-gate attributional Life Cycle Assessment of avocado production in Peru by small and medium-sized producers, under multiple scenarios to provide insights for enhancing environmental performance and including a sensitivity and uncertainty analysis.
Open linkAuthor(s): Red Peruana Ciclo de Vida y (Español) Alejandro Gallego-Schmid, Ricardo Rebolledo-Leiva, Leonardo Vásquez-Ibarra, Alvaro Elorrieta-Mendoza, Denisse Milagros Paredes Cotohuanca, Claudia E. Henninger, Ana Belén Guerrero
(Español) 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.
Open linkAuthor(s): Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe y (Español) David Baptista de Sousa
(Español) 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.
Open linkAuthor(s): Ian Vázquez Rowe, Patricia Mogrovejo Román, Eizo Muñoz Sovero, (Español) Pablo Gonzalez, Karin Bartl, Isabel Quispe Trinidad y (Español) vazquez
(Español) Limited studies have been conducted in Latin America related to the environmental profile of cocoa and chocolate production using Life Cycle Assessment (LCA). The current study conducts a cradle-to-gate LCA of the production of organic chocolate products in Peru, considering cocoa cultivation practices by a group of 21 female producers located in central Peru in the year 2022. Data were collected on-site at cultivation sites and processing plant using questionnaires with the technical staff. Beyond fossil and biogenic emissions linked to cultivation, transport of dried cocoa, and manufacturing activities at the chocolate producing plant, carbon capture on fields by cocoa and shading trees was modeled and included in the carbon balance. A total of 8 impact categories were selected, considering different environmental compartments. Results for global warming using the main scenario show a range of values from 4.33 kg CO2eq per kilogram of final chocolate product to 4.88 kg CO2eq. Most impacts are derived from the production of dry cocoa beans and, to a lesser extent, upstream sugarcane production. However, important differences were evident when the individual cocoa producers were analyzed, with agroforestry systems presenting lower greenhouse gas (GHG) emissions than cocoa monocrops. Regarding water scarcity, the activities at the chocolate processing plant were found to contribute more than water use at the cocoa cultivation sites. For other impact categories, toxicity emissions at the cultivation site were relatively low given the organic characteristics of the fields, which do not use conventional pesticides. The post-harvest management of the cocoa pods (i.e., composting) is a critical source of GHG emissions. Hence, adequate composting conditions maintain methane emissions low, but direct return of the pods to the field can generate a substantial increase in GHG emissions. Carbon sequestration from above ground biomass, mainly from shading and cocoa trees, appears to mitigate an important fraction of these emissions if shading is homogeneous and sufficiently dense across the fields.
Author(s): Diana Ita Nagy, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
(Español) 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.
Open linkAuthor(s): Ian Vázquez Rowe
(Español) 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.
Open linkAuthor(s): Ian Vázquez Rowe
(Español) 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.
Open linkAuthor(s): Luis Izquierdo Horna, Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe
(Español) 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.
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