3. Producción
Browse
12 results
Search Results
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Unveiling the energy consumption–food waste nexus in households: A focus on key predictors of food waste generation(Springer, 2024-07-01)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. Graphical (Figure presented.). - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Low energy and carbon hydroponic tomato cultivation in Northern Spain: Nutritional and environmental assessment(American Chemical Society, 2024-01-15)The agri-food sector is one of the most impactful on the environment in terms of greenhouse gas emissions and is one of the largest consumers of energy and natural resources. In this context, the objective of this study was to evaluate the environmental impacts of hydroponic tomatoes cultivated in northern Spain using a waste product as biomass to heat the greenhouses and solar energy for powering the irrigation system to identify their main environmental hotspots and improvement measures. For this purpose, life cycle assessment (LCA) has been used. The functional units (FUs) chosen were 1 kg of tomatoes and an alternate FU based on nutrition, e.g., NRF9.3. The influence of including biogenic CO2 emissions has been considered using a “-1/+1″ approach to assess the uptake and release of biogenic carbon throughout the whole life cycle. The main results showed that greenhouse gas emissions varied between 1.4 kg CO2 equiv and 2.5 kg CO2 equiv considering biogenic carbon, whereas the total energy demand of the production of hydroponic tomatoes was 9.7 MJ. Fertilization and the greenhouse structure were identified as the main contributors to environmental burdens; hence, improvement opportunities were focused on these critical points. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Integrating the water-energy-food nexus and LCA + DEA methodology for sustainable fisheries management: A case study of Cantabrian fishing fleets(Elsevier B.V., 2024-11-01)The fishing sector constitutes an important source of economic revenue in northern Spain. In this context, various research studies have focused on the application of the five-step Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methodology to quantify environmental impacts of fishing systems. However, some of them have used environmental indicators that focus on individual environmental issues, hindering the goal of achieving integrated resource management. Therefore, in this study, the Water-Energy-Food (WEF) Nexus is employed as an integrative perspective that considers the synergies and trade-offs between carbon footprint, energy requirements, and water demand. The main objective of this study is to evaluate the operational efficiency and environmental impacts of Cantabrian fishing fleets. To this end, the combined use of LCA and DEA, along with the WEF Nexus, was applied to the Cantabrian purse seine fleet. DEA matrices were generated using the LCA-derived WEF nexus values as inputs to calculate efficiency scores for each vessel. Subsequently, based on the efficiency projections provided by the DEA model, a new impact assessment was performed to understand the eco-efficiency and potential environmental benefits of operating at higher levels of efficiency within this fleet. The average efficiency of the fleet was above 60 %. Inefficient units demonstrated a greater potential to reduce their environmental impacts (up to 65 %) by operating according to efficiency projections. Furthermore, the results revealed a strong dependence of environmental impacts on one of the operational inputs, i.e., fuel consumption. These findings highlight the significance of embracing holistic approaches that combine technical, economic, and social factors to achieve a sustainable balance in fisheries systems. In this regard, the five-step LCA + DEA method applied in conjunction with the WEF Nexus emerged as a suitable tool for measuring operational and environmental objectives. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identifying environmental impacts linked to the production of plant-based spreads in Peru using life cycle assessment(Elsevier B.V., 2024-06-01)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 fertilizer 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Applying the multi-dimensional damage assessment (MDDA) methodology to the Cumbre Vieja volcanic eruption in La Palma (Spain)(Springer Science and Business Media B.V., 2024-12-01)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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Are Peruvians moving toward healthier diets with lower environmental burden? Household consumption trends for the period 2008–2021(John Wiley and Sons Inc, 2024-10-01)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. This article met the requirements for a gold/gold JIE data openness badge described at http://jie.click/badges. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analyzing the behavior of beachgoers in the city of Lima and their relationship with potential plastic emissions(Elsevier Ltd, 2024-12-01)Beach littering is a source of marine plastic waste accumulation. This is particularly so in overcrowded beaches in the Global South in which cleaning measures are scarce or sporadic and lack of waste management systems can increase plastic release. In the current study we focus on the importance of the behavior shown by beachgoers and how their conduct relates to the amount of plastic that potentially ends up entering littoral ecosystems. Transportation services to beaches, sports, food, and beverage containers are analyzed through a 24-question survey performed to 500 beachgoers in 4 beaches (i.e., Venecia, Punta Negra, Punta Hermosa and San Bartolo) located in the megacity of Lima, Peru, in February 2022. The data obtained were then processed to understand the differences in behavior across different beaches. Moreover, a K-means algorithm was used to identify representative beachgoer profiles. The results showed a dichotomous behavior between two groups of beaches, in which the size group of beachgoers, transportation mode, accommodation, food consumption patterns or the use of reusable containers are some of the main differences between the two groups. No major differences were identified in terms of age distribution across the different beaches, but group sizes were higher in Punta Negra and Villa El Salvador. The K-means algorithm suggests that the surveyed population can be grouped into three main categories, of which two correspond mainly to higher socioeconomic beachgoers in the beaches of Punta Hermosa and San Bartolo. Overall, single use plastic for food and beverages appears as one of the main sources of plastic pollution across beaches and groups, although other sources of plastic emission should not be underestimated. Finally, the three beachgoer profiles identified are useful to implement targeted policies to minimize the environmental impacts of these profiles. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The use of artificial intelligence algorithms to detect macroplastics in aquatic environments: A critical review(Elsevier B.V., 2024-10-01)The presence of macroplastic (MP) is having serious consequences on natural ecosystems, directly affecting biota and human wellbeing. Given this scenario, estimating MPs' abundance is crucial for assessing the issue and formulating effective waste management strategies. In this context, the main objective of this critical review is to analyze the use of machine learning (ML) techniques, with a particular interest in deep learning (DL) approaches, to detect, classify and quantify MPs in aquatic environments, supported by datasets such as satellite or aerial images and video recordings taken by unmanned aerial vehicles. This article provides a concise overview of artificial intelligence concepts, followed by a bibliometric analysis and a critical review. The search methodology aimed to categorize the scientific contributions through temporal and spatial criteria for bibliometric analysis, whereas the critical review was based on generating homogeneous groups according to the complexity of ML and DL methods, as well as the type of dataset. In light of the review carried out, classical ML techniques, such as random forest or support vector machines, showed robustness in MPs detection. However, it seems that achieving optimal efficiencies in multiclass classification is a limitation for these methods. Consequently, more advanced techniques such as DL approaches are taking the lead for the detection and multiclass classification of MPs. A series of architectures based on convolutional neural networks, and the use of complex pre-trained models through the transfer learning, are currently being explored (e.g., VGG16 and YOLO models), although currently the computational expense is high due to the need for processing large volumes of data. Additionally, there seems to be a trend towards detecting smaller plastic, which need higher resolution images. Finally, it is important to stress that since 2020 there has been a significant increase in scientific research focusing on transformer-based architectures for object detection. Although this can be considered the current state of the art, no studies have been identified that utilize these architectures for MP detection. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The Role of Developing and Emerging Economies in Sustainable Food Systems(Springer Science and Business Media Deutschland GmbH, 2023-11-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Revising Regionalized Water Scarcity Characterization Factors for Selected Watersheds Along the Hyper-Arid Peruvian Coast Using the AWARE Method(Springer, 2023-11-01)The Peruvian coast is known for its low water availability and high water demand, which is mainly satisfied by groundwater sources. The current study develops regionalized water scarcity characterization factors (CFs) based on the available water remaining (AWARE) method for eight selected watersheds located along the hyper-arid Peruvian coast. Furthermore, the paper proposes water scarcity CFs for groundwater in six watersheds, which are not available in current methods. Methods: The regionalization of water scarcity CFs along the Peruvian coast was based on the following: (i) national delineation of hydrological units (HUs), (b) use of primary data on water availability and demand provided by official water balance reports and national databases, (c) use of the ecological flow values recommended by national authorities, and (d) proposal of specific water scarcity CFs for groundwater. Moreover, the results of the updated CFs were compared to those from the original CFs from AWARE. A sensitivity analysis, including recalculated CFs based on future climate change scenarios, was also provided. Thereafter, water scarcity impacts for grape and avocado production available in the scientific literature were recalculated based on previous studies with the new CFs. Results and discussion: Results revealed significant differences between updated and original water scarcity CFs in both geographical and temporal (i.e., monthly) terms. Hence, updated CFs showed that all watersheds selected experience high levels of water scarcity, especially from June to October, a more realistic scenario than that showed with original water scarcity CFs when confronted to water availability values. Meanwhile, water scarcity CFs for groundwater showed intense pressure all year round for the three main sources of groundwater (i.e., Chillon, Rimac, and Lurin aquifers) that provide water to the city of Lima, whereas only one groundwater watershed showed low water scarcity (i.e., Mala-Omas aquifer). Conclusions: Updated water scarcity CFs provide a watershed-based quantification of water scarcity in the hyper-arid Peruvian coast, which we consider more realistic as compared to the original CFs. Moreover, the water scarcity CFs proposed for groundwater allow estimating the pressure over aquifers in a higher level of disaggregation, which can be used to monitor the overexploitation of groundwater sources in an area that is highly dependent on these water sources.