Modelo híbrido de sistemas energéticos para la evaluación del uso de energías renovables

Carlos Iván Torres González (2020, [Tesis de maestría])

En este trabajo proponemos un modelo híbrido para evaluar diferentes escenarios de generación de electricidad con energías renovables que maximiza el bienestar social desde la perspectiva económica contemplando un enfoque técnico sobre la estructura de costos de producción de electricidad. Adicionalmente, realizamos 2 simulaciones del modelo propuesto al sistema eléctrico de Baja California Sur para 10 períodos, contemplando 4 escenarios de producción limpia diferentes. De los resultados observados en ambas simulaciones podemos remarcar 2 puntos en términos de políticas públicas. El primer punto es la importancia de tener múltiples generadores que funcionen con combustibles renovables si se desea producir una proporción significativa de electricidad con FER. El segundo punto es el trade-off entre bienestar y emisiones de CO2. Los resultados sugieren que el aumento del consumo de electricidad es un elemento importante para aumentar el bienestar social. A su vez, el aumento de consumo eléctrico implica un aumento de producción, y por tanto un aumento de emisiones de CO2. Los resultados de la segunda simulación sugieren que con el aumento de la capacidad de generación limpia y costos eficientes, se pueden alcanzar niveles de bienestar casi iguales a los tradicionales, pero con la mitad de emisiones de CO2.

Electric power production -- Effect of renewable energy sources on -- Mexico -- Baja California Sur (State) -- 2015 -- Mathematical models. Carbon dioxide mitigation -- Effect of renewable energy sources on -- Mexico -- Baja California Sur (State) -- 2015 -- Mathematical models. CIENCIAS SOCIALES CIENCIAS SOCIALES

El impacto de la violencia en los flujos migratorios procedentes de Guatemala

Thania Berenice Hernández Alarcón (2021, [Tesis de maestría])

Con este trabajo buscamos entender cómo la violencia en el lugar de origen de una persona puede motivar su decisión de migrar. La aproximación teórica al fenómeno de la migración sugiere que la provisión relativa de bienes públicos es un factor en el análisis costo beneficio mediante el cual el agente evalúa la rentabilidad de la migración. Desde esta perspectiva, la búsqueda de beneficios pecuniarios, como un mayor salario, es compatible con la búsqueda de beneficios no pecuniarios, como mayores niveles de seguridad. Nos interesamos por evaluar lo anterior para el caso de Guatemala. Sirviéndonos de la variación trimestral de trecientos veintinueve municipios en una ventana de once años buscamos evidencia de que la tasa de migración de personas de origen guatemalteco que buscan empleo en México o Estados Unidos se correlaciona de manera positiva con la tasa de homicidios en sus municipios de origen. Nuestros resultados sugieren que esto se cumple y que aumentos en los niveles de violencia homicida pueden propiciar desplazamientos laborales.

Guatemala -- Emigration and immigration -- Effect of violence on -- Econometric models United States -- Emigration and immigration -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES

Impacto de COVID-19 sobre el consumo eléctrico de las PYMES de la Zona Metropolitana de Aguascalientes

Alonso Darío Pizarro Lagunas (2021, [Tesis de maestría])

La irrupción de COVID-19 en el escenario mundial no sólo se convirtió en una crisis de salud pública sino una crisis económica que tuvo efectos heterogéneos en muchos países en el mundo. En particular, muchas economías experimentaron una fuerte contracción en su producto interno bruto debido en gran parte a las medidas de distanciamiento social y restricción de actividades no esenciales que los países adoptaron para proteger la salud de sus habitantes. Esto afectó al sector eléctrico, ya que muchas industrias disminuyeron su consumo energético. En México, las pequeñas y medianas empresas representan una parte importante del consumo eléctrico de la industria. En este sentido, tomando una muestra representativa de pequeños y medianos establecimientos de la Zona Metropolitana de Aguascalientes estudiamos el comportamiento del consumo eléctrico de estas empresas notando que hubo caídas significativas del consumo eléctrico cuando irrumpió la pandemia en marzo de 2020 en la ZMA. Además, notamos que la caída en consumo eléctrico fue más pronunciada para establecimientos en el sector de servicios que establecimientos en el sector de comercios durante la pandemia. Además, se concluye que las disminuciones en la jornada laboral jugaron un papel importante en esta contracción, mientras que las medidas como digitalización y reducción de empleados no estuvieron relacionadas con la variación de consumo eléctrico en estos pequeños y medianos establecimientos.

Small business -- Energy consumption -- Effect of COVID-19 Pandemic, 2020- on -- Aguascalientes (Mexico) -- Econometric models. COVID-19 Pandemic, 2020- -- Aguascalientes (Mexico) -- Economic aspects. CIENCIAS SOCIALES CIENCIAS SOCIALES

Contrasting spatial patterns in active-fire and fire-suppressed mediterranean climate old-growth mixed conifer forests

Danny L. Fry  (2014, [Artículo])

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha-1, and occupied 27-46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11-20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥56%) in large patches (≥10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types.

article, climate, controlled study, ecosystem fire history, forest structure, geographic distribution, geographic mapping, land use, mathematical computing, mathematical model, Mexico, spatial analysis, taiga, United States, comparative study, conife CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA

Optimizing nitrogen fertilizer and planting density levels for maize production under current climate conditions in Northwest Ethiopian midlands

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

This study determined the most effective plating density (PD) and nitrogen (N) fertilizer rate for well-adapted BH540 medium-maturing maize cultivars for current climate condition in north west Ethiopia midlands. The Decision Support System for Agrotechnology Transfer (DSSAT)-Crop Environment Resource Synthesis (CERES)-Maize model has been utilized to determine the appropriate PD and N-fertilizer rate. An experimental study of PD (55,555, 62500, and 76,900 plants ha−1) and N (138, 207, and 276 kg N ha−1) levels was conducted for 3 years at 4 distinct sites. The DSSAT-CERES-Maize model was calibrated using climate data from 1987 to 2018, physicochemical soil profiling data (wilting point, field capacity, saturation, saturated hydraulic conductivity, root growth factor, bulk density, soil texture, organic carbon, total nitrogen; and soil pH), and agronomic management data from the experiment. After calibration, the DSSAT-CERES-Maize model was able to simulate the phenology and growth parameters of maize in the evaluation data set. The results from analysis of variance revealed that the maximum observed and simulated grain yield, biomass, and leaf area index were recorded from 276 kg N ha−1 and 76,900 plants ha−1 for the BH540 maize variety under the current climate condition. The application of 76,900 plants ha−1 combined with 276 kg N ha−1 significantly increased observed and simulated yield by 25% and 15%, respectively, compared with recommendation. Finally, future research on different N and PD levels in various agroecological zones with different varieties of mature maize types could be conducted for the current and future climate periods.

Maize Model Planting Density CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE MODELS SPACING NITROGEN FERTILIZERS YIELDS

Energy and economic efficiency of climate-smart agriculture practices in a rice–wheat cropping system of India

Manish Kakraliya Deepak Bijarniya Parbodh Chander Sharma ML JAT (2022, [Artículo])

Intensive Tillage Conventional Rice–Wheat Systems Energy Efficiency On-Farm Studies Climate-Smart Agricultural Practices CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE-SMART AGRICULTURE RICE WHEAT CROPPING SYSTEMS

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Oportunidad de aplicación de la metodología FRONT END LOADING en la expansión de gasoductos en el sureste mexicano: una evaluación

Opportunity to apply the front end loading methodology in the expansion of gas pipelines in the mexican southeast: an evaluation

Raúl Enrique Trejo Alvarado Luis Rolando Méndez Miguel (2023, [Artículo])

Con la finalidad de impulsar el desarrollo de la región sureste de México, la actual administración del gobierno federal se ha propuesto la ampliación de la red nacional de gasoductos hacia esa zona del país, con el fin de suministrar energía a los megaproyectos de la región. No obstante, estas obras presentan actualmente retrasos, evidenciando la necesidad de metodologías de gestión que permitan solucionar este problema de raíz. Una de las metodologías más prometedoras en esta materia es la front-end loading (FEL), ampliamente aplicada en el sector extractivo y energético. El propósito del articulo estriba en evaluar la posibilidad de aplicar la metodología FEL a los proyectos de expansión del Sistema Nacional de Gasoductos en el sureste mexicano.

To boost the development of the southeast region of Mexico, the current federal government administration has proposed the expansion of the national gas pipeline network to this area of the country, to supply energy to the region's mega-projects. However, these projects are currently experiencing delays, demonstrating the need for management methodologies to solve this problem at its root. One of the most promising methodologies in this area is front-end loading (FEL), which has been widely applied in the extractive and energy sector. The aim of this paper is to evaluate the possibility of applying the FEL methodology to the expansion projects of the National Gas Pipeline System in the southeastern México.

Gas natural Sector energético Front end loading (FEL) Evaluación de proyectos Sureste mexicano Natural gas Energy sector Project evaluation Mexican southeast INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Transición de leña a gas licuado a presión (GLP) en el sur de México, oportunidad para la mitigación del cambio climático en la región menos desarrollada del país

Transition from biomass to LP gas in southern Mexico, an opportunity for climate change mitigation in the least developed region in the country

Elio Guarionex Lagunes Díaz María Eugenia González Rosende Alfredo Ortega Rubio (2015, [Artículo])

"En los estados del sur de México, entre un 25% y un 55% de los hogares dependen de la leña para cocinar, lo cual trae consecuencias en el ambiente, el desarrollo y la salud. No obstante, el conocimiento de estas consecuencias y la migración hacia combustibles modernos ha permanecido relegada de las políticas de desarrollo. En este trabajo, partiendo de una descripción del panorama de uso de leña en el país y su importancia como fuente de energía, se presenta una aproximación para estimar ahorros en emisiones de CO2 logrables por la transición a gas licuado a presión (GLP), los cuales pueden alcanzar 3.14 Mt CO2e, 26% menos que el escenario base. Se finaliza con una discusión de la transición hacia combustibles modernos, las barreras que la impiden y los logros y fallos de la distribución de estufas ahorradoras de leña, la principal iniciativa gubernamental para aliviar el consumo de leña en el país."

"Between 25% and 55% of households in southern Mexico depend on biomass for cooking, which carries serious consequences on the environment, development and health. In spite of the knowledge of these consequences, transition from biomass to modern fuels has remained outside energy and development policies. In the present work, after describing the panorama of fuelwood use in the country and its importance as an energy source, an approach is presented for estimating CO2 savings achievable by transition to pressurized liquefied gas (LP). These savings can reach 3.14 Mt CO2e, 26% less than the baseline scenario. At the end we discuss on the transition to modern fuels in Mexico, the barriers that hinder it and the achievements and failures of the distribution of fuelwood saving cookstoves, as the only and most important governmental initiative to alleviate biomass use, comparing it with other priorities in the government's agenda."

Transición energética, cambio climático, política energética. Energy transition, climate change, energy policy. CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO METEOROLOGÍA CONTAMINACIÓN ATMOSFÉRICA CONTAMINACIÓN ATMOSFÉRICA