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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, 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, Ocean-Based Sources of Plastic Pollution: An Overview of the Main Marine Activities in the Peruvian EEZ(Elsevier Ltd, 2023-04-01)Marine-based activities are a critical source of plastic waste into the ocean. This is particularly important in countries with a competitive fishing industry, such as Peru. Thus, this study aimed to identify and quantify the major flows of plastic waste accumulating in the ocean from ocean-based sources within the Peruvian Economic Exclusive Zone. A material flow analysis was elaborated to analyze the stock of plastic and its release to the ocean by a set of Peruvian fleets, including the fishing industry, merchant vessels, cruises, and boating vessels. Results show that in 2018 between 2715 and 5584 metric tons of plastic waste entered the ocean. The fishing fleet was the most pollutant, representing approximately 97 % of the total. Moreover, fishing gear loss represented the highest single-activity contribution, although other sources, such as plastic packaging and antifouling emissions, have the potential to become vast sources of marine plastic pollution. - 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.