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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, 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, 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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Machine Learning Approach to Understand How Accessibility Influences Alluvial Gold Mining Expansion in the Peruvian Amazon(Elsevier Ltd, 2023-06-01)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.