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Peruvian efforts to contain COVID-19 fail to protect vulnerable population groups
(Elsevier, 2020-11-01)
Peru is arguably providing a robust governmental response in the initial stages of the COVID-19 outbreak, with early lockdown measures and the implementation of relatively ambitious economic safety nets to protect families and enterprises. Despite this initial optimism, structural deficiencies in the public health system, high informality in the labor market, the new wave of migrants from Venezuela and the extremely diverse cultural characteristics of many areas exacerbate the number of potentially highly vulnerable groups that may be left out of these safety nets unless additional efforts are enforced to improve social coverage. In this discussion we aim to identify some of these groups, highlighting the main challenges they face during the outbreak and proposing certain mitigation measures to balance the social policy response.
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Climate action and food security: strategies to reduce GHG emissions from food loss and waste in emerging economies
(Elsevier, 2021-07-01)
Peru struggles to upgrade its waste management, with landfilling only just overtaking open dumpsters as the main disposal method. Despite the benefits of this transition, including reduced environmental impacts to water and soil, previous studies demonstrated that greenhouse gas (GHG) emissions may increase if adequate levels of technological sophistication are not implemented. Considering that 58% of municipal solid waste (MSW) is organic, it seems plausible that a relevant portion of emissions can be linked directly to food loss and waste (FLW) management. This study aims to determine the GHG emissions mitigation potential in FLW compared to the current baseline scenario in 24 Peruvian cities, by modelling alternative technologies to treat organic MSW. Life cycle modelling was performed using the waste-LCA software EASETECH. Five treatment scenarios were modelled: i) open dumping; ii) landfilling with no gas treatment; iii) landfilling with landfill gas treatment; iv) landfilling with energy recovery; and, v) anaerobic digestion. GHG emissions of FLW generation proved to be substantially higher than those for FLW treatment. However, if sophisticated technologies are implemented in FLW treatment, an annual reduction of up to 1.56 Mt CO2eq could be attained. Moreover, despite the health and environmental benefits of a transition to optimized diets, in which, for example, meat consumption is reduced and vegetables are boosted, an important increase in FLW and, therefore, an increase in GHG emissions in the treatment phase is shown. However, if certain technologies, such as energy recovery or anaerobic digestion, were implemented, most carbon losses would be avoided.
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Environmental footprint of critical agro-export products in the Peruvian hyper-arid coast: a case study for green asparagus and avocado
(Elsevier, 2021-11-19)
Peru has become one of the world's main agricultural hubs for a wide range of fruits and vegetables. Two of these products, avocado and green asparagus, have raised attention in recent years in the international scene from an environmental perspective due to the high amounts of water they require, as well as the long air and marine freighting distances to export these products to Europe, Asia or the US. Consequently, the aim of the current study was to perform an environmental assessment of these two products using two life-cycle methods: carbon and water footprint. For the latter, water scarcity, acidification, eco-toxicity and eutrophication impact categories have been selected for assessment. Inventory data were gathered from six different companies located in different regions of the hyper-arid Peruvian coast. The results report that the products are not carbon intensive and are in line with other similar plant-based products. Conversely, the hyper-arid conditions of the cultivation sites require a large volume of groundwater to fulfill the needs of the crops. Interestingly, even though this may lead to overexploitation of groundwater resources in the absence of appropriate management policies, the low mobility of pollutants, namely pesticides, constitutes a natural barrier to protect the degradation of natural water bodies. Similarly, highly technified irrigation systems have allowed minimizing the amounts of water used per hectare. In conclusion, results from this study may be useful in more concise environmental assessment studies on food products and diets, considering the consumption of these Peruvian products in many countries in the world. Furthermore, results are also important at regional level since they depict the carbon and water performance of these products and can also be accompanied by cross-cutting certification schemes, including Product Environmental Footprint Category Rules Guidance.
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Exploring machine learning techniques to predict deforestation to enhance the decision-making of road construction projects
(Wiley, 2021-08-24)
Land use changes (LUCs), which are defined as the modification in the use of land due to anthropogenic activities, are important sources of GHG emissions. In this context, understanding future trends of LUCs, such as deforestation, in a spatial manner is relevant. The main objective of this study is to generate a deforestation prediction model for a given period of time (i.e., 2002–2017 and 2010–2017) to estimate the potential carbon emissions associated with different anthropogenic variables in the Peruvian Amazon using machine learning (ML) algorithms. This study was motivated in the analysis of a road project previously studied using life cycle assessment (LCA). Models using neural networks and random forest algorithms were trained and evaluated in a fully cloud-based environment using Google Earth Engine. ML-related results demonstrated that random forest is a quicker and straightforward response to model the system under study, especially considering that data do not require additional processing during the modeling and prediction stages. Predicted results suggest that expected road expansion may be related to considerable carbon emissions in the future. Calculated values are relevant especially if the mitigation efforts that Peru has complied with in the Paris Agreement are considered. The increased complexity of the framework is justified since it allows identifying the location of hotspots and may potentially complement the utility of LCA in policy support in the areas of territorial planning and tropical road expansion.
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Developing a methodology to quantify mismanaged plastic waste entering the ocean in coastal countries
(John Wiley and Sons Inc, 2022-12-01)
Marine plastic accumulation has gained international attention in recent years. Sources, pathways, and environmental impacts are being currently studied to understand the complex interactions during waste, especially plastic, transportation to the sea. Rivers have been identified as debris corridors allowing transportation of mismanaged waste. However, there is also evidence of waste accumulation in river basins, suggesting they can also act as sinks. Thus, assuming a uniform and continuous transportation of waste through rivers towards the ocean may signify an oversimplification. This study proposes a methodology to estimate plastic release to the ocean, considering a more detailed characterization of each river basin, including natural attributes and manmade constructions that may act as barriers or boosters for this release. The methodology is exemplified using a case study for the Region of Piura, Peru, and estimating a range of 4.2 to 13.9 kg/person/year of plastic waste reaching the Pacific coast during 2018. These results, when compared with the existing literature, demonstrate more conservative estimations. This methodology is presented as a useful tool that can be easily applied to develop more accurate mismanaged waste dissipation along different compartments. Supplementary Information: The online version of this article (doi:10.1111/jiec.13349) contains supplementary material, which is available to authorized users.
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Climate change mitigation potential of transitioning from open dumpsters in Peru: Evaluation of mitigation strategies in critical dumpsites
(Elsevier B.V., 2022-11-10)
Waste management is a critical policy towards the reduction of environmental impacts to air, soil and water. Many Latin American countries, however, lack a correct waste management system in many cities and rural areas, leading to the accumulation of unmanaged waste in illegal or unregulated dumpsites. The case of Peru is of interest, as it hosts 5 of the 50 largest dumpsites in the world. An erratic waste management compromises climate actions for Peru to commit with the Paris Agreement, as no correct closure systems are established for these dumpsites. Therefore, the main objective of this study is to assess the contribution of the past and present biodegradable waste produced and disposed of in the most critical open dumpsters to the overall annual greenhouse gas (GHG) emissions of Peru using the IPCC model. Thereafter, the climate change mitigation potential of possible dumpsite closure strategies based on a selection of technologies, including economic feasibility, were estimated. Results show that cumulative GHG emissions in 2018 for the 24 critical dumpsites evaluated added up to 704 kt CO2 eq. and a cumulative value of 4.4 Mt CO2 eq. in the period 2019–2028, representing over 40 % of solid waste emissions expected by 2030. Mitigation potentials for these emissions tanged from 91 to 970 kt CO2 eq. in the ten-year period depending on the mitigation strategies adopted. The costs of these strategies are also discussed and are expected to be of utility to complement Peru's waste management commitments in the frame of the Paris Agreement.
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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.
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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.
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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.
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Applying random forest to forecast municipal solid waste generation from household fuel consumption
(Elsevier BV, 2025-09-01)
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 year 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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