Author(s): Gustavo Larrea Gallegos, Ian Vázquez Rowe
(Español) 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.
Open linkAuthor(s): Karen Biberos Bendezú, Úrsula Cárdenas Mamani, Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe
(Español) Governments in the Global South have recently started to align their public procurement regulations considering Green Public Procurement (GPP) guidelines to achieve Sustainable Development Goal 12. In this context, it is important to establish environmental criteria to help decision making after analyzing the variety of options available in the market. Thus, using as examples two of the most acquired products in public procurement in Peru: Medium-density particleboard melamine furniture and paper offset, the aim of this paper is to determine the main environmental hotspots and therefore show the path to foster GPP in Peru. To achieve this goal, a Life Cycle Assessment was carried out considering it is a suitable environmental management tool to quantify environmental impacts. For this, a set of scenarios were modeled and compared for each of the two products selected, covering different geographical and technological options that are currently purchased by the Peruvian government. Results demonstrated that it is possible to attain considerable reductions in the environmental impact of the products analyzed if the main critical stages throughout their life cycle are identified and adequate solutions are applied to avoid burden shifting. Moreover, we argue that it is important for developing countries to carry out case-specific life-cycle inventories as they provide higher-quality information based on the particular characteristics of regional or local industries, allowing the determination of more realistic environmental impact mitigation benchmarks. Nevertheless, the inclusion of lifecycle-based criteria in GPP must be performed cautiously, avoiding command and control regulations, as numerous challenges remain in terms of capacity building, environmental awareness, and environmental information, and transparency in emerging and developing economies. Integr Environ Assess Manag 2021;00:1–15. © 2021 SETAC
Open linkAuthor(s): Red Peruana Ciclo de Vida y (Español) GETEC [Grupo de Gestión y Tecnología en la Construcción de Edificaciones y Obras Civiles], GERDIS[Grupo de Gestión de Riesgos de Desastres en Infraestructura Social y Vivienda de Bajo Costo]
(Español) Building information modeling (BIM) is an emerging technology that improves visualiza- tion, understanding, and transparency in construction projects. Its use in Latin America and the Caribbean (LA&C), while still scarce, is developing in combination with multi-criteria decision- making (MCDM) methods, such as the choosing by advantages (CBA) method. Despite the holistic nature of MCDM methods, the inclusion of life cycle environmental metrics is lagging in construc- tion projects in LA&C. However, recent studies point toward the need to optimize the synergies between BIM and life cycle assessment (LCA), in which a method like CBA could allow improving the quality of the decisions. Therefore, the main objective of this study is to integrate LCA and CBA methods to identify the effect that the inclusion of environmental impacts can have on decision- making in public procurement, as well as comparing how this final decision differs from an exclu- sively LCA-oriented interpretation of the results. Once the LCA was performed, a set of additional criteria for the CBA method were fixed, including transparency, technical, and social indicators. Thereafter, a stakeholder participative workshop was held in order to gather experts to elucidate on the final decision. The methodology was applied to a relevant construction sector problem mod- elled with BIM in the city of Lima (Peru), which consisted of three different construction techniques needed to retrofit educational institutions. Results from the LCA-oriented assessment, which was supported by Monte Carlo simulation, revealed a situation in which the masonry-based technique showed significantly lower environmental impacts than the remaining two options. However, when a wider range of technical, social, and transparency criteria are added to the environmental indicators, this low-carbon technique only prevailed in those workshop tables in which environ- mental experts were present and under specific computational assumptions, whereas teams with a higher proportion of government members were inclined to foster alternatives that imply less bu- reaucratic barriers. Finally, the results constitute an important milestone when it comes to including environmental factors in public procurement in LA&C.
Download publication (709.70 KB)Author(s): Red Peruana Ciclo de Vida y (Español) otros
(Español) The availability of freshwater is one of the biggest limitations and challenges of food production, as freshwater is an increasingly scarce and overexploited resource in many parts of the world. Therefore, the concept of water footprint (WF) has gained increasing interest, in the same way that the generation of food loss and waste (FLW) in food production and consumption has become a social and political concern. Along this line, the number of studies on the WF of the food production sector is currently increasing all over the world, analyzing water scarcity and water degradation as a single WF indicator or as a so-called WF profile. In Spain, there is no study assessing the influence of FLW generation along the whole food supply chain nor is there a study assessing the different FLW management options regarding the food supply chain’s WF. This study aimed to assess the spatially differentiated WF profile for 17 Spanish regions over time, analyzing the potential linkages of FLW management and water scarcity and water degradation. The assessment considered compliance and non-compliance with the Paris Agreement targets and was based on the life cycle assessment approach. Results are highlighted in a compliance framework; the scenarios found that anaerobic digestion and aerobic composting (to a lesser extent) had the lowest burdens, while scenarios with thermal treatment had the highest impact. Additionally, the regions in the north of Spain and the islands were less influenced by the type of FLW management and by compliance with the Paris Agreement targets.
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(Español) Purpose: Marine litter, mostly plastics, is a growing environmental problem. Environmental decision makers are beginning to take actions and implement regulations that aim to reduce plastic use and waste mismanagement. Nevertheless, life cycle assessment (LCA), a tool commonly used to assist environmental decision making, does not yet allow for considering the consequences of plastic waste leaked into the environment. This limits the application of LCA as a tool for highlighting potential tradeoffs between impact categories and the relative significance of their contribution on a specific Areas of Protection (AoP). A coordinated research effort to cover various parts of the marine litter impact pathway is required to ultimately produce characterisation factors that can cover this research gap. Here, we design a consistent and comprehensive framework for modelling plastic litter impact pathways in LCIA models. This framework is to support such coordinated research progress towards the development of harmonized pathways to account for impacts of plastic litter, specifically to the marine environment. The framework includes an overview of life cycle inventory requirements (leakage to the envi- ronment; a focus of other research efforts), and a detailed description of possible marine litter impact pathways, modelling approaches and data(-type) requirements. We focus on marine plastic litter and consider the potential contribution of different impact pathways to overall damage in the main operational AoPs, as well as recently proposed ones.
Results and conclusions: The proposed framework links inventory data in terms of kg plastic leaked to a specified environmental compartment (air, terrestrial, freshwater, marine) to six AoPs: ecosystem quality, human health, socio-economic assets, ecosystem services, natural heritage and cultural heritage. The fate modelling step, which includes transportation, fragmentation and degradation processes, is common to all included impact pathways. Exposure and effect modelling steps differentiate between at least six exposure pathways, e.g. inhalation, ingestion, entanglement, invasive species rafting, accumulation, and smothering, that potentially compromise sensitive receptors, such as ecosystems, humans, and manmade structures. The framework includes both existing, e.g. human toxicity and ecotoxicity, and proposed new impact categories, e.g. physical effect on biota, and can be used as a basis for coordinating harmonized research efforts.
Author(s): Eduardo Parodi Gonzales Prada, Ramzy Kahhat Abedrabbo, Ian Vázquez Rowe
(Español) Assessing disaster impacts is the pathway to attain informed decision making to mitigate dam- ages. Currently, these impacts are generally analyzed excluding the environmental consequences of disasters. Thus, this study proposes a novel quantitative method, named multi-dimensional damage assessment (MDDA), that integrates the disaster-related environmental impacts with economic and social losses. For this, Life Cycle Assessment was used to measure environmental impacts at the endpoint level for the human health area of protection. The unit of assessment used to merge the three damage dimensions was the disability-adjusted life year equivalent (DALYeq). The damages exerted by floods in Peru linked to El Nin ̃o in recent decades were selected as the main case study. Furthermore, other natural disasters (e.g., earthquakes) were included in the assessment for the sake of comparability. The results show that El Nin ̃o floods in Peru in 1982–83 and 1997–98 presented higher damage per capita, approximately 2.8 times higher, than the event in 2017. Additionally, the assessment showed that economic damages are the most relevant in El Nin ̃o floods, whereas social damages are those prevalent for earthquakes. The results demonstrate that MDDA is an effective measurement for the purpose of damage comparison and, therefore, to implement mitigation strategies. The proposed methodology will allow the development of disaster risk mitigation strategies that will cover all damage dimensions and enable the adoption of improved public policies. Finally, MDDA can be applied to compute any complex array of damages that humans may suffer or infringe as a consequence of their interaction with the environment.
Download publication (2.07 MB)Author(s): Ian Vázquez Rowe y y otros
(Español) Action on reducing food loss and waste (FLW) is imperative to mitigate the impacts of climate change worldwide and to achieve the Sustainable Development Goals on food security, hunger eradication, and sustainable production and consumption. Next year (2022) will be the UN summit of food systems (“the COP for food”), as articles in this special issue illustrate, FLW will stay as one of the major levers to pull for food system transformation and sustainable consumption.
Open linkAuthor(s): Ian Vázquez Rowe, Kurt Ziegler Rodríguez, Ramzy Kahhat Abedrabbo y María Margallo, Rubén Aldaco
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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