Author(s): Joan Sanchez Matos, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
Open linkAuthor(s): Ian Vázquez Rowe, (Español) Claudia Cucchi Quispe, Eduardo Parodi Gonzales Prada, Ramzy Kahhat Abedrabbo y []
(Español) Volcanic events with an important affectation of urban areas and other land areas with important human activity have been rare in Europe in the past century. This has led to a lack of comprehensive analysis of the social, economic and environmental damages that these types of events can cause on specific human communities. In the present study, we apply an industrial ecology approach to calculate the damage linked to the Cumbre Vieja volcanic eruption in the Canary Islands in September 2021. Therefore, the main objective was to apply the multi dimensional damage assessment (MDDA) methodology to quantify the degree of damage that has been exerted by the eruption in the island of La Palma (Spain) through the inclusion of environmental damage endpoints with other sustainable development variables (i.e., social and economic dimensions). Data were obtained from different sources, including the cadastre of La Palma, local data on derived health, as well as data obtained from the global ecosystem dynamics investigation of NASA, among other sources. Thereafter, damage endpoints were all converted to disability-adjusted life years (DALYs). Results show that direct gaseous emissions from the volcano were responsible for a significant amount of total DALYs, above 90% in all scenarios, followed by damage linked to economic losses, as well as social losses related to morbidity. Other environmental damages played a minor part in the total damage exerted by the volcano. The results demonstrate the importance of air quality indicators in the aftermath of an eruption in densely populated areas; in contrast, the impact associated with infrastructure loss played a minor role in total damage. Although challenges remain when providing a holistic quantification of total damage linked to volcanic disasters, the MDDA method constitutes a promising systematic standardized and transparent damage quantification tool that allows computing a deterministic damage evaluation that can aid in natural hazard risk assessment. In fact, it is considered that the method has the potential to be used as a holistic decision tool to aid in mitigating disaster risk.
Open linkAuthor(s): Joan Sanchez Matos, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
(Español) Peru is one of the most diverse countries in the world in terms of food production, but also suffers a wide range of food security challenges, including malnutrition, the impact of natural hazards, and rising food prices. People living in poverty conditions are the main victims of these problems, which trigger undernutrition, obesity, and diet-related non-transmittable diseases. Despite these challenges, Peru lacks historical food intake data. Therefore, in the current study, we assess the diet quality evolution in the period 2008–2021 based on apparent household purchases extracted from the National Household Survey. The results reveal significant variations in the consumption of certain food items and groups, and the consequences of these changes are discussed in environmental and human health terms. The consumption of lower environmental impact animal protein, such as chicken, eggs, and marine fish, has increased by 37%, 69%, and 29%, respectively; whereas the consumption of high environmental impact foods, such as beef and other red meat, has decreased. Moreover, consumption of less processed carbohydrate sources (e.g., legumes, fruits, and vegetables) has risen, while refined sugar and sugar sweetened beverages have decreased significantly (almost 45%). Regional differences were also visible; hence, cities on the Northern coast and the Amazon basin had similar consumption habits, whereas Central/Southern coastal and Andean cities had closer consumption patterns. On average, this improvement was reflected in the increase in calories (9.9%) and macronutrient intake (up to 15%), but at the socioeconomic level, food inequality persists, with consumption of many food groups below minimum thresholds in lower socioeconomic strata.
Download publication (3.10 MB)Author(s): Luis Izquierdo Horna, Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe
(Español) In most cities worldwide, household food waste constitutes a significant portion of municipal solid waste (MSW). However, its management often proves inadequate due to the insufficient resources allocated to waste management systems, the omission of the resource potential in MSW, and the lack of recognition of household food waste drivers for forecasting generation in specific geographical contexts. This research aims to identify social, economic, and environmental variables serving as proxies to forecast household food waste generation. To achieve this, a multiple linear regression model was proposed to assess the relationship between cooking fuel type (i.e., liquefied petroleum gas, natural gas, and electricity), land use categories (i.e., commercial, industrial, and residential), population density, expenditure on in-house food consumption, and household food waste generation. Three alternate modeling scenarios were considered based on available data, with Lima, Peru, serving as a case study. The results indicate that the combined consumption of liquefied petroleum gas and natural gas, and electricity consumption, along with residential land use, were the most influential variables. Finally, for a comprehensive understanding of the studied phenomenon, it is crucial to analyze and consider the intricate dynamics of societal consumption patterns.
Open linkAuthor(s): (Español) Claudia Cucchi Quispe, Ian Vázquez Rowe, Mario Echevarría, Ramzy Kahhat Abedrabbo y []
(Español) Plant-based spread products, such as margarine, are made up of a combination of diverse ingredients, many times arriving from different parts of the world. This makes their environmental impact challenging to compute. In Latin America, despite efforts in recent years to enlarge the number of food items that have been analyzed from an environmental perspective, many processed products remain unexplored. In this context, the main objective of the current study was to determine the environmental impacts of a set of five plant-based spread products in Peru using life cycle assessment. For this, primary data were collected from the main margarine producer up to the gate of the agroindustrial plant ready for distribution. Methodological choices, such as allocation, the computation of land use changes (LUCs) or agricultural management variability, were an important subset of variables to be considered in the life cycle modeling and accounted for through scenario and sensitivity analyses. Results demonstrated that greenhouse gas (GHG) emissions related to margarine production in Peru range from 1.66 to 6.00 kg CO2eq per kilogram of product, in a similar range to other studies in the literature. LUCs accounted for the highest contribution to GHG emissions, whereas crude oil extraction, as well as on field fer- tilizer emissions were the other main contributors. In other impact categories, plant protection agents were relevant in toxicity indicators, fertilization in eutrophication and transport in air quality-related categories. These results constitute a benchmark for the production of plant-based products in Latin America and are useful for attaining cleaner production, as well as for the optimization of ingredients and packaging design.
Open linkAuthor(s): Joan Sanchez Matos, Ian Vázquez Rowe, Ramzy Kahhat Abedrabbo
(Español) International trade in fishery and aquaculture products is an important means of providing feed and food for different countries around the world. However, it is also responsible for multiple environmental impacts, namely climate change, as well as novel environmental aspects, such as plastic emissions, through its entire life cycle. In fact, plastic emissions are gaining increasing attention due to their presence in a variety of environmental compartments, especially in marine ecosystems. Hence, this study estimated the carbon footprint and the plastic emissions into the oceans from fishing and aquaculture trade between the European Union (EU) and South America (SA), based on a life cycle perspective. The results reveal that there is an imbalance both in terms of mass and carbon emissions between the import and export flows. SA exports eight-fold more aquaculture and fishing products (877,000 t) than those it imports (112,000 t), emitting twelve-fold more greenhouse gasses (2.9 million metric tons CO2eq.) than the EU (242,000 t CO2eq.), demonstrating the existence of seafood trade imbalances between the two regions. The entire trading releases into the ocean at least 263 t of macroplastic, and 45 t of microplastics from the fishing phase. This suggests the importance of the environmental impacts of the trade flows of aquaculture and fishing products, and the urgent need to decrease carbon emissions and provide more sustainable alternatives to plastic materials in fishing gear.
Open linkAuthor(s): Ian Vázquez Rowe
The White Paper aims to take stock of existing policy and regulatory frameworks regarding the prevention and mitigation of microplastic in coastal aquaculture input chains in APEC region. A desk study and expert workshops involving 42 contributors from 12 APEC economies were carried to collect the required data and information to develop the paper. This White Paper found that there are almost negligible regulatory frameworks to monitor and prevent microplastics in APEC’s coastal aquaculture input chains. Public discourses and research related to the issues are also limited. This White Paper recommends the continuation of public discourses and research activities to support the development of a comprehensive policy related to microplastic issues in coastal aquaculture. The comprehensive policy could be used by APEC economies to develop their own regulatory measures to ensure and promote the safety of seafood products from coastal aquaculture of APEC region.
Download publication (4.87 MB)Author(s): Gustavo Larrea Gallegos, Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe, Eduardo Parodi Gonzales Prada
(Español) Alluvial small-scale gold mining (ASGM) mining in the Amazon is expanding fiercely, generating severe environmental degradation, which includes the fast disappearance of primary forests in a highly biodiverse area of the world. Different factors motivate the growth of mining in the areas and understanding this expansion is important to safeguard protected areas or implement strategies to mitigate the related social and environmental impacts. Thus, the goal of this study is to apply machine learning techniques to explore gold mining expansion in Madre de Dios, in the Peruvian Amazon, and to identify possible future hotspots of these activities. Using an unsupervised learning algorithm and a random forest classification model, past expansion trends were analyzed and an explicit geo-spatial model was built. Results demonstrate that proximity to infrastructure is not always indicative of high mining probability. In fact, when analyzing the spatial distribution of model accuracy, it is observed that model performance decreases in clusters where accessibility and mining activity showed opposite trends. In contrast, the models yield accuracies greater than 0.9 when accessibility-related variables stand out as the most important. The model, which is flexible and reproducible, demonstrates to be useful to enhance decision making when implementing geo-spatial policies to address the problem of ASGM expansion in the Amazon.
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