Sergio Arboleda University
Recent publications
Bus rapid transit (BRT) vehicles are common microenvironments in urban areas. In some cities, these BRT vehicles are diesel-powered, which makes them highly pollutant. Recent studies report high levels and exposure risk to particulate matter in BRT vehicles. Nevertheless, extensive research has yet to be published, including gaseous pollutants (e.g., CO). Nevertheless, extensive research including gaseous pollutants (e.g., CO) has not been published. This research aims to evaluate the self-pollution of BRT buses in terms of exhaust gasses. For this, measurements and computational fluid dynamics (CFD) were used. Results suggest that pollutant concentrations stay low during most of the trips. However, some areas of the buses have significant swings and peaks due to the transit cycle. Here, we used CFD modeling to evaluate the dispersion of the exhaust CO inside and outside the bus. CFD results show that the bus rear has the highest concentrations, with a mean self-pollution ratio of 12%. Additionally, we developed a method based on the source-receptor relationship to quantify the impact of exhaust emissions reduction on self-pollution, showing that the technological replacement of current diesel buses would reduce self-pollution and, therefore, passenger exposure. Finally, since modeling results may be inaccurate, an uncertainty analysis was developed using the Monte Carlo method to obtain a confidence interval of 90% for the variables linked to the self-pollution.
Unlabelled: 2020 presented the ideal conditions for studying the air quality response to several emission reductions due to the COVID-19 lockdowns. Numerous studies found that the tropospheric ozone increased even in lockdown conditions, but its reasons are not entirely understood. This research aims to better understand the ozone variations in Northern South America. Satellite and reanalysis data were used to analyze regional ozone variations. An analysis of two of the most polluted Colombian cities was performed by quantifying the changes of ozone and its precursors and by doing a machine learning decomposition to disentangle the contributions that precursors and meteorology made to form O3. The results indicated that regional ozone increased in most areas, especially where wildfires are present. Meteorology is associated with favorable conditions to promote wildfires in Colombia and Venezuela. Regarding the local analysis, the machine learning ensemble shows that the decreased titration process associated with the NO plummeting owing to mobility reduction is the main contributor to the O3 increase (≈50%). These tools lead to conclude that (i) the increase in O3 produced by the reduction of the titration process that would be associated with an improvement in mobile sources technology has to be considered in the new air quality policies, (ii) a boost in international cooperation is essential to control wildfires since an event that occurs in one country can affect others and (iii) a machine learning decomposition approach coupled with sensitivity experiments can help us explain and understand the physicochemical mechanism that drives ozone formation. Supplementary information: The online version contains supplementary material available at 10.1007/s11869-023-01303-6.
El Ministerio de Ambiente, es competente para adoptar medidas que aseguren la protección de las especies de la flora silvestre, tomar las previsiones que sean del caso para la defensa de las especies en extinción o en peligro de serlo. En ese marco, debe intervenir en el manejo, aprovechamiento, transporte y comercialización de especies e individuos de la flora silvestre y de sus productos primarios, de propiedad pública o privada. Así las cosas, y como medida de control y vigilancia, el código de recursos naturales exige que todo producto forestal primario que entre al territorio Nacional, salga o se movilice dentro de él debe estar amparado por permiso. Para la movilización de los productos forestales se requieren documentos autorizatorios, y estos variaran dependiendo de los productos forestales, que de acuerdo a la legislación se clasifican en: 1) salvoconducto único en línea 2) certificado de movilización y 3) remisión de movilización.
La investigación realizada sobre el compromiso ambiental de 60 instituciones de educación superior (IES) colombianas evaluadas en 2017 permitió conocer su vinculación y compromiso con la Agenda 2030 y los Objetivos de Desarrollo Sostenible (ODS). A partir de este hallazgo, el propósito del artículo es presentar la relación de las IES con los ODS de la esfera planeta con base en el conocimiento y la práctica. Se identificaron así los cinco ODS que priorizan las instituciones: primero el 4 “Educación de calidad”, segundo el 6 “Agua limpia y saneamiento”, tercero el 12 “Producción y consumo responsables”, cuarto el 11 “Ciudades y comunidades sostenibles” y quinto el 3 “Salud y bienestar”. El análisis se realiza a partir del enfoque de sistemas ambientales institucionales (SAI), el cual integra cinco ámbitos: 1) políticas y participación ambiental, 2) docencia y formación ambiental, 3) investigación ambiental, 4) proyección socioambiental, 5) gestión y ordenamiento ambiental de los campus. El ODS 4 se configura como el más relevante para la educación superior. En los ámbitos de gobierno y formación ambiental los aportes se asocian principalmente a la meta 4.7, de educación para el desarrollo sostenible. En el ámbito de la investigación ambiental, el objetivo más relacionado con los proyectos de las IES es el 15 (ecosistemas terrestres); en gestión ambiental, los ODS más relacionados fueron el 11 (ciudades y comunidades sostenibles) y el 12 (producción y consumo); y en cuanto a extensión y proyección socioambiental, el 4 y el 11. Se concluye que cada uno de los ámbitos analizados evidencia el compromiso de las IES con la Agenda 2030, y aunque las acciones desarrolladas en su concepción inicial no nacen en todos los casos en respuesta a dicha agenda, las IES sí están aportando a diferentes ODS y a sus metas, siendo el eje la educación de calidad propuesta en el ODS 4.
Climate change might affect energy production and therefore the energy security of a country or region. This situation may impact renewable energy sources such as hydro power, leading to consequences on energy transition strategies. This might be critical in sensitive regions to climate change, one of them being the Caribe and northern South America. Since there are numerous energy systems based on sensitive technologies worldwide, it is necessary to introduce techniques to analyze the effects of climate change on different possible energy transition paths. The goal of this study is to develop and assess a method to analyze one of the most critical effects faced by climate change for societies worldwide: the sensitivity of the energy systems to climate change. This is especially critical in developing countries, in locations where temperatures will strongly increase in the following years. To assess this effect, this study proposes a vulnerability index (VI) to evaluate the vulnerability of an on-grid electricity system to climate change at the national and regional scales. This index was assessed using a Monte-Carlo method for uncertainty. The case of Colombia, a country with a system based on hydropower (> 70%) is used to illustrate the method. VI is based on variables related to climate change, the energy matrix, and vulnerability. Results show that the regions with the larger vulnerability correspond to the more energy-demanding ones. The VI for these regions is greater than 50% of the maximum possible vulnerability; meanwhile, the vulnerability of the whole country was estimated as 43%.
Abstract: In today's globalized and dynamic world, companies face pressures related to high-quality product offerings that meet customer expectations, with minimum variability. Likewise, they deal with complex systems, such as industrial processes. The objective of this article was to design a five-phase model of the DMAIC cycle by integrating the six sigma and system dynamics approaches for variability reduction in critical quality characteristics. Model validation was carried out via a case study in the electrolytic tin plating process, in a Colombian metal-mechanics company. Thus, the current process was simulated and various scenarios were analyzed, that which would benefit the company the most was selected. The results show significant quality improvement by way of the reduction of variability in the coating thickness, and profit increases achieved through poor quality and reprocessing cost reductions. The proposed model serves as a financial viability tool, given the implementation of a six- sigma project, by guiding management to determine the best scenario for investments in the process, so as to obtain results that benefit companies, in terms of both profits and product quality.
Throughout the years, wildfires have negatively impacted ecological systems and urban areas. Hence, reinforcing territorial risk management strategies against wildfires is essential. In this study, we built an early alert system (EAS) with two different Machine Learning (ML) techniques to calculate the meteorological conditions of two Colombian areas: (i) A 3D convolutional neural net capable of learning from satellite data and (ii) a convolutional network to bias-correct the Weather Research and Forecasting (WRF) model output. The results were used to quantify the daily Fire Weather Index and were coupled with the outcomes from a land cover analysis conducted through a Naïve-Bayes classifier to estimate the probability of wildfire occurrence. These results, combined with an assessment of global vulnerability in both locations, allow the construction of daily risk maps in both areas. On the other hand, a set of short-term preventive and corrective measures were suggested to public authorities to implement, after an early alert prediction of a possible future wildfire. Finally, Soil Management Practices are proposed to tackle the medium- and long-term causes of wildfire development, with the aim of reducing vulnerability and promoting soil protection. In conclusion, this paper creates an EAS for wildfires, based on novel ML techniques and risk maps.
Polyvinyl chloride (PVC) is widely used in industrial applications, such as construction and clothing, owing to its chemical, physical, and environmental resistance. Owing to the previous characteristics, PVC is the third most consumed plastic worldwide and, consequently, an increasing waste accumulation-related problem. The current study evaluated an in-house collection of 61 Actinobacteria strains for PVC resin biodegradation. Weight loss percentage was measured after the completion of incubation. Thermo-gravimetric analysis was subsequently performed using the PVC incubated with the three strains exhibiting the highest weight loss. GC-MS and ionic exchange chromatography analyses were also performed using the culture media supernatant of these three strains. After incubation, 14 strains had a PVC weight loss percentage higher than 50% in ISP-2 broth. These 14 strains were identified as Streptomyces strains. Strains 208, 250, and 290 showed the highest weight loss percentages (57.6–61.5% range). The thermal stability of PVC after bacterial exposure using these three strains was evaluated, and a modification of the representative degradation stages of nonincubated PVC was observed. Additionally, GC-MS analysis revealed the presence of aromatic compounds in the inoculated culture media, and ionic exchange chromatography showed chloride release in the supernatant. A mathematical relation between culture conditions and PVC weight loss was also found for strains 208 and 290, showing an accuracy up to 97.99%. These results highlight the potential of the freshwater-derived Streptomyces strains as candidates for the PVC biodegradation strategy and constitute the first approach to a waste management control scale-up process.
One of the main applications of small satellites is Earth observation. CubeSats and different kinds of nanosatellites usually form constellations that obtain images mainly using an optical payload. There is a massive amount of data generated by these satellites and a limited capacity of download due to volume and mass constraints that make it difficult to use high-speed communication systems and high-power systems. For this reason, it is important to develop satellites with the autonomy to process data on board. In this way, the limited communication channel can be used efficiently to download relevant images containing the required information. In this paper, a system for the satellite on-board processing of RGB images is proposed, which automatically detects the cloud coverage level to prioritize the images and effectively uses the download time and the mission operation center. The system implements a Convolutional Neural Network (CNN) on a Commercial off-the-Shelf (COTS) microcontroller that receives the image and returns the cloud level (priority). After training, the system was tested on a dataset of 100 images with an accuracy of 0.9 and it was also evaluated with CubeSat images to evaluate the performance of a different image sensor. This implementation contributes to the development of autonomous satellites with processing on board.
Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.
For decades, Fuzzy Sets Theory (FST) has been consistently developed, and its use has spread across multiple disciplines. In this process of knowledge transfer, fuzzy applications have experienced great diffusion. Among them, Fuzzy Analytic Hierarchy Process (fuzzy AHP) is one of the most widely used methodologies today. This study performs a systematic review following the PRISMA statement and addresses a bibliometric analysis of all articles published on fuzzy AHP in journals indexed in Web of Science, specifically in Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). The analyzed database includes 2086 articles published between 1994 and 2022. The results show the thematic clusters, the evolution of the academic conversation and the main collaboration networks. The main contribution of this article is to clarify the research agenda on fuzzy AHP. The results of the study allow academics to detect publication opportunities. In addition, the evidence found allows researchers and academics setting the field’s agenda to advise the editors of high-impact journals on gaps and new research trends.
The primary goal of this study is to assess the opportunities that students have to access and handle digital training scenarios while displaying the skills needed to use information and communication technologies on a digital ecosystem. The methodological approach has a mixed design. A questionnaire containing 28 items is applied and an online discussion forum is set up. The sample consists of 280 students from the Faculty of Educational Sciences at the University of La Guajira (Colombia). The results indicate that there is a gap in access to technology, since only 45.7% of the participants claim to have a personal computer or a tablet, while only 39.3% can regularly access the Internet. It is concluded that during the COVID-19 pandemic there were considerable gaps in accessing and using digital tools; however, students developed skills to more efficiently use the technologies they had access to.
Systemic disruptions are becoming more continuous, intense, and persistent. Their effects have a severe impact on the economy in volatile, uncertain, complex, and ambiguous (VUCA) environments that are increasingly transversal to productive sectors and activities. Researchers have intensified their academic production of multiple-criteria decision-making (MCDM) in recent years. This article analyzes the research agenda through a systematic review of scientific articles in the Web of Science Core Collection according to the Journal Citation Report (JCR), both in the Social Sciences Citation Index (SSCI) and in the Science Citation Index Expanded (SCIE). According to the selected search criteria, 909 articles on MCDM published between 1979 and 2022 in Web of Science journals in the business and management categories were located. A bibliometric analysis of the main thematic clusters, the international collaboration networks, and the bibliographic coupling of articles was carried out. In addition, the analysis period is divided into two subperiods (1979–2008 and 2009–2022), establishing 2008 as the threshold, the year of the Global Financial Crisis (GFC), to assess the evolution of the research agenda at the beginning of systemic disruptions. The bibliometric analysis allows the identification of the motor, basic, specialized, and emerging themes of each subperiod. The results show the similarities and differences between the academic debate before and after the GFC. The evidence found allows academics to be guided in their high-impact research in business and management using MCDM methodologies to address contemporary challenges. An important contribution of this study is to detect gaps in the literature, highlighting unclosed gaps and emerging trends in the field of study for journal editors.
Customizing environmental assessments to the particularities of the type of environment is crucial for implementing the precautionary principle. This paper uses the SHIELD model (Susceptibility to Human Interventions for Environmental Licensing Determination) in the context of geomorphology for the effective management of coastal environments. This paper describes the customization of the SHIELD model for tropical coastal environments as a way of validating a specific kind of environment. The assessment translates expert knowledge into technical criteria for the environmental control of human interventions through fuzzy logic computations. This assessment identified 21 geomorphological processes across six categories. Moreover, computation of the parameters resulted in a database of susceptibility measures for 4524 interactions. These quantitative results could guide future environmental impact studies of coastal environments, considering licensing instrument requirements. The SHIELD model approach, illustrated here on tropical coastal environments, offers a technical alternative for improving the environmental control of anthropogenic impacts from a geomorphological perspective.
In places with complex topography, the reproduction of atmospheric dynamics is challenging and resource-demanding. Recently, machine learning has been successfully implemented to forecast pollution and weather variables. LSTM (long short-term memory) networks have the potential to improve the forecasting precision in different theoretical fields. Despite this advantage, they have not been widely used in the tropics for this purpose. This research aims to implement a LSTM to forecast PM2.5 and meteorological variables in a tropical mountainous city. The model was trained with 7 years of data from the local air quality monitoring network. The implemented model forecasts 42 days, evaluated using statistical scores and benchmarks. More than 95% of PM2.5 values, radiation (99%), air temperature (98%), relative humidity (95%), wind speed (94%), and the u-component (91%) have excellent or good benchmarks. The v-component and the wind direction got the lowest percentage of excellent or good values (50%). We compared our results with other models that have focused on forecasting these variables in similar places and observed that the LSTM approach results are the best, especially for PM2.5 and wind direction. We found its accuracy can be affected by rapid changes in the tendency of the data that do not occur as a consequence of the diurnal tide. The LSTM model was validated as a tool to predict meteorological variables and PM2.5 (24 h in advance) in a tropical mountainous city and can be used as a reliable input in air quality early alert systems.
This paper analyzes the spatio-temporal variations, and exceedances of the PM2.5 concentrations in Northwestern South America at different scales to assess the implemented policies and identify the involved phenomena. Through reanalysis and ground-based data, we found that high PM2.5 levels in most cities of the region are caused by wildfires and local emissions, including the capital cities of Venezuela, Ecuador, Colombia, and Panamá. In-situ measurements suggest that the majority of the cities comply with the local but not with the WHO guidelines, indicating that local annual limits should be more restrictive. Two peaks in the daily variations of PM2.5 (related to vehicle emissions) and also a steeper decrease around noon (associated with an increase in wind speed and in the boundary layer height) were identified. The trend-analysis shows that Bogotá and Medellín have a decreasing PM2.5 annual-trend (between −0.8μgm⁻³ and −1.7μgm⁻³) that corresponds to effective policies. In contrast, Cali has a positive annual-trend (0.8μgm⁻³) most likely because of Short-Range Transport produced by a northerly-flow from a highly polluted neighboring city, which also affects Cali's PM2.5 diurnal cycle, or by local-dynamics. The exceedances show that the policies are working on an annual but not at a daily time-scale. These results serve as a first input for additional studies, with the aim of gaining a better understanding of the contaminant before adapting current policies or implementing new policies and measures that need to include a joint international, regional, and inter-city efforts regarding pollution transport.
La evolución de los modelos de organización humana ha permitido el surgimiento de modernas estructuras estatales que, para el caso colombiano, se cristalizan en el Estado social de derecho adoptado en la Constitución Política de 1991. Este modelo de Estado busca la garantía real y efectiva de los preceptos constitucionales a partir de, entre otros, el rol del juez constitucional como garante judicial de la Constitución, sus derechos y principios. Los jueces usan su discrecionalidad para superar las ambigüedades, vaguedades, antinomias o cualquier otro conflicto presente en el sistema jurídico colombiano con el fin de tomar la mejor decisión posible conforme a los preceptos constitucionales. A la luz de este importante rol del juez, y de su facultad discrecional, en el presente escrito se estudiarán dos sentencias de unificación de la Corte Constitucional de Colombia, en las que se determinará si la Corte aplicó incorrectamente el Estado social de derecho, ello en el marco del presunto ejercicio discrecional realizado por el administrador de justicia. Lo dicho se desarrollará a través de una metodología dogmática con la que se analizarán las decisiones escogidas, junto con fuentes normativas, jurisprudenciales y doctrinarias para determinar si, en los casos de estudio, se tomaron decisiones contrarias a los principios derivados del texto constitucional colombiano como consecuencia de un ina-decuado uso de la discrecionalidad, específicamente como consecuencia de la errada aplicación de la cláusula del Estado social de derecho.
Haiti has become a scenario of convergence between the political and the criminal as a combination for territorial control and security configuration. Using process tracing, we wanted to find what were the motivations for hiring a group of mercenaries with the aim of getting rid of an increasingly authoritarian president. Thus we identify critical points in Haitian history regarding the symbiosis between crime and political institutions, which permit us to construct causal mechanisms to identify that, among other things, Haiti is a phantom state, as we call it in our research, because it has a nominal and supplanted political structure in which competition between different groups who seek to assume political authority has led to a limited, fragmented, delegated and authoritarian presence of the state among the population and the territory. Consequently, we find that the use of force has not belonged exclusively to the state, it has been divided into different oligopolies of violence and the Haitian state is only one more actor in the criminal complex of the country, where state institutions are the mechanisms with criminal organizations to generate criminal dynamics of territorial control and profit. Based on the above, we consider that, as the government of Jovenel Moïse had allied with the strongest gangs and weakened political groups and criminal rivals, the mercenaries were the instrument to break the authoritarian government of Moïse. In effect, the magnicide was the product of a plan to depose the president, undertaken by political leaders in complicity with the country’s judiciary to curb the concentration of executive power.
La competencia digital es un activo que debe poseer el docente para interactuar en el mundo digital. En este artículo se analizaron los marcos de referencia recientes sobre la competencia digital con el propósito de identificar las principales habilidades, aptitudes y roles que deben ser asumidos por los profesores en el siglo XXI. Se realizó un mapeo sistemático de la literatura que consideró varios aspectos: el aprendizaje de las tecnologías de la información y la comunicación, la pedagogía, la comprensión de las competencias digitales y su interrelación con las competencias investigativas. Los resultados indican que el humanismo digital es un eje central e insustituible de la práctica docente contemporánea y que el uso de las tecnologías en los procesos de aprendizaje es un aspecto importante a considerar en la formación de los profesores. Se concluye que el éxito del docente está dado por la cultivación de competencias tecnológicas, por la inclusión de estrategias creativas, investigativas e innovadoras en las aulas, y que el humanismo y la cultura son fundamentales para su desarrollo profesional.
El presente artículo reflexivo da cuenta del proyecto de investigación “Propuesta Creación del Centro de I+D+i para le CEA”, y tiene por objetivo explorar y analizar el manejo de buscadores especializados, de bases de datos para el desarrollo de la producción académica y científica por parte de docentes e investigadores en Colombia, y comprobar el uso de este tipo de recursos tecnológicos para el desarrollo de su producción académica o científica mediante una encuesta realizada a 164 docentes de seis universidades privadas acreditadas, y cuatro Instituciones de educación superior (IES) públicas del sector militar, elegidos al azar, involucrados en actividades de investigación. Para ello, este artículo se aborda desde cuatro aspectos: primero, revisión teórica de universidades acreditadas en el país hasta el 2019; segundo, caracterización de los grupos de investigación e investigadores reconocidos en Colombia para establecer la participación de las IES, tomando como base el análisis estadístico que de ellos hace Colciencias con los resultados de su convocatoria 833 de 2018:de, , tercero, exploración general de las bases de datos más conocidas, describiendo las de acceso abierto y las que requieren inscripción para su adquisición; cuarto, aplicación de una encuesta a una muestra seleccionada de docentes investigadores con el fin de identificar las estrategias usadas por ellos para la recolección de la información académica y científica, y establecer una visión general del uso de las bases de datos científicos en la academia.
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1,755 members
Peter Bunyard
  • Instituto de Ciencias Ambientales
Maribel Anaya
  • school of engineering
Margot Salas-Brown
  • Escuela de Ciencias Exactas e Ingeniería
Ellie Anne López-Barrera
  • -IDEASA- Instituto de Estudios y Servicios Ambientales
Bogotá, Colombia