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Item type:Publication, Prevalence of microplastics in the ocean in Latin America and the Caribbean(Elsevier, 2021-12-12)The release of microplastics to the ocean is an increasing global environmental concern. The specific characteristics of the Global South (e.g., widespread mismanaged waste and wastewater) make this an even greater challenge. The current study performed a critical review related to the prevalence of microplastics in the ocean in Latin America and the Caribbean, analyzing also the possible sources of microplastics release to the marine environment. A majority of the studies assessed point towards mismanaged waste, inland or offshore, as well as mismanaged wastewater as critical sources of plastic pollution into the ocean. However, there is a need to delve into the effects that these microplastics are generating on local biota and human health. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Understanding the evolution of cities through urban stocks: A comparative analysis of Andean and coastal urban areas in Peru(John Wiley and Sons Inc, 2024-08-01)The evolution of cities follows distinct patterns that connect to the cultural and socioeconomic aspects of their populations and can be understood by studying their urban stocks. This paper examines the evolution of construction materials stocks (MS) in the building sector in five urban areas in Peru. The study employed a bottom-up methodology and focused on the city of Abancay in the Peruvian Andes, comparing it to the coastal cities of Chiclayo, Tacna, and San Isidro, as well as Lince. Additionally, regression models were employed to examine the influence of socioeconomic factors associated with urban stock. The research highlights a transition from residential building stock to distinct patterns of socioeconomic development, with urban population and economic growth emerging as pivotal drivers of material stock variation. Notably, large coastal cities like Chiclayo, Tacna, San Isidro, and Lince exhibit significantly higher concrete MS per capita, albeit with varying growth rates. In contrast, Abancay, with lower income levels, displays a higher per capita level of adobe MS, reflecting its historical connection to Peru's heartland. The correlation of urban stock components with the human development index (HDI) emphasizes the latter's significance in understanding the trends of the stocks of the different construction materials that constitute a city. By examining MS in various locations, unique Peruvian traits are unveiled, offering insights for urban development in the Global South. These findings provide valuable guidance for aligning urban stock growth and related environmental burdens with socioeconomic development, fostering sustainability, and promoting rational planning for economic growth.3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enabling mechanisms for circularity in Latin America and the Caribbean(KeAi Communications Co., Ltd., 2024-08-22)Within Latin America’s strategic importance in the global value chain, circular economy strategies emerge as pivotal pathways for the region. By identifying key enabling mechanisms (namely regulatory frameworks, assessing and monitoring socio-economic metabolism, and financial instruments), this paper unveils the imperative for actions in fostering a circularity transition, and preserving traditional circular economy practices for Latin American and the Caribbean countries in the upcoming decade. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Quantifying and mapping informal and formal building material stocks in Lima(IOP Publishing, 2025-09-30)Construction materials are essential for meeting societal needs in urban areas; however, they pose significant challenges for decarbonization, particularly in rapidly growing cities that struggle to meet the needs of all their citizens, such as those in the Global South (GS). This research develops and applies a GIS-based methodology to create an urban material stock map for Lima, Peru, encompassing both nonresidential and residential buildings, with the latter categorized into informal and formal housing. This study combines block-level spatial data with a refined definition of informality that better captures the nuances of reality while acknowledging its limitations, along with an extensive housing typology to calculate the material stocks present in the city. Material intensity (MI) factors were developed for each housing type, allowing for the estimation of material stocks across Lima's districts. The MI of informal housing is up to 70% less than that of formal housing. The results indicate that informal settlements comprise a substantial share of the housing (50%) and residential stock (31%) in the city. The research also highlights spatial disparities in material accumulation and their correlation with income inequality. This approach provides a replicable framework for other cities in the GS, addressing the urgent need for local data and tailored methodologies to inform sustainable urban planning and decarbonization strategies.Scopus© Citations 2 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Circular Economy in the Global South: Co-creating a research agenda from the Industrial Ecology Society(Wiley, 2026-04-01)The Global South faces unique sustainability challenges especially around the use and management of resources, providing a timely opportunity to understand and adapt Circular Economy (CE) approaches and initiatives, to chart a research agenda for these regions. During the 12th International Conference on Industrial Ecology (IE), ISIE Singapore 2025, we hosted the first special session to unpack the variety of research and key issues related to CE in the Global South. The session aimed to create shared learning and co-creation of a research agenda to prioritize the necessary elements for an effective, inclusive, and just CE transition. A total of 24 participants contributed to the session, representing 16 nationalities. In this paper, we discuss the key outcomes from the session, focusing on the most pressing research gaps, desirable characteristics of a comprehensive CE research agenda, and enablers needed to ensure alignment with both global priorities and local realities. Three core areas emerged as priorities for the IE community's CE research agenda in the Global South: (1) improving data integrity and availability, especially addressing data collection methodologies for uncovering blind-spots such as those related to the informal economy; (2) combining quantitative IE tools with qualitative, transdisciplinary approaches to better address complex circular challenges; and (3) recognizing and integrating cultural practices and ancestral knowledge drawing on CE principles. By articulating these priorities, our IE society can support more grounded, context-sensitive, and inclusive CE research practices that respond to the specific needs and contributions of the Global South.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 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.2