Artículos Ingeniería

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Leadership Development in Women STEM Students: The Interplay of Task Behaviors, Self-Efficacy, and University Training
(2024) Coluccio, Giuliani; Muñoz-Herrera, Sebastián; Adriasola, Elisa; Escobar, Elizabeth
This study explores the relationship between task-oriented behaviors, self-efficacy, and leadership emergence in women STEM students, grounded in the context of prototypical leadership theory and self-efficacy theory. Prototypical leadership theory emphasizes the alignment of leadership behaviors with group expectations, which, in STEM fields, are often task-oriented. The research examines how task-oriented behaviors, such as planning, decision-making, and supervision, influence women’s self-perception of leadership ability and their subsequent emergence as leaders. Our results show a positive relationship between task-oriented behaviors and self-efficacy and a positive relationship between self-efficacy with leader emergence, with academic experience further ngthening this link. As students’ progress through their programs, engaging in more teamwork and leadership tasks, their self-efficacy enhances, leading to stronger leadership emergence. Also, we found an indirect effect from task-oriented behavior to leader emergence via self-efficacy. These findings have significant implications for fostering leadership in women, particularly in STEM. The study calls for educational programs to enhance opportunities for women to develop these behaviors early on, ensuring their growth into leadership roles in STEM fields
Study of the Suitability of a Personal Exposure Monitor to Assess Air Quality
(2024) Aljofi, Halah E.; Bannan, Thomas J.; Flynn, Michael; Evans, James; Topping, David; Matthews, Emily; Diez, Sebastian; Edwards, Pete; Coe, Hugh; Brison, Daniel R.; Tongeren, Martie van; Johnstone, Edward D.; Povey, Andrew
Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2s (PLFs) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM2.5), 10 μm or less (PM10), and nitrogen dioxide (NO2), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r < 0.4). Moderate correlation was observed for one PLF unit at the indoor location and two units at the roadside location when measuring PM2.5, but not for PM10 and NO2 concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R2 values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs.
Transcriptome Data Analysis Applied to Grapevine Growth Stage Identification
(2024) Altimiras, Francisco; Pavéz, Leonardo; Pourreza, Alireza; Yañez, Osvaldo; González-Rodríguez, Lisdelys; García, José; Galaz, Claudio; Leiva-Araos, Andres; Allende-Cid, Héctor
In agricultural production, it is fundamental to characterize the phenological stage of plants to ensure a good evaluation of the development, growth and health of crops. Phenological characterization allows for the early detection of nutritional deficiencies in plants that diminish the growth and productive yield and drastically affect the quality of their fruits. Currently, the phenological estimation of development in grapevine (Vitis vinifera) is carried out using four different schemes: Baillod and Baggiolini, Extended BBCH, Eichhorn and Lorenz, and Modified E-L. Phenological estimation requires the exhaustive evaluation of crops, which makes it intensive in terms of labor, personnel, and the time required for its application. In this work, we propose a new phenological classification based on transcriptional measures of certain genes to accurately estimate the stage of development of grapevine. There are several genomic information databases for Vitis vinifera, and the function of thousands of their genes has been widely characterized. The application of advanced molecular biology, including the massive parallel sequencing of RNA (RNA-seq), and the handling of large volumes of data provide state-of-the-art tools for the determination of phenological stages, on a global scale, of the molecular functions and processes of plants. With this aim, we applied a bioinformatic pipeline for the high-throughput quantification of RNA-seq datasets and further analysis of gene ontology terms. We identified differentially expressed genes in several datasets, and then, we associated them with the corresponding phenological stage of development. Differentially expressed genes were classified using count-based expression analysis and clustering and annotated using gene ontology data. This work contributes to the use of transcriptome data and gene expression analysis for the classification of development in plants, with a wide range of industrial applications in agriculture.
The Water Management Impacts of Large-Scale Mining Operations: A Social and Environmental Perspective
(2024) Arenas-Collao, Katherine; Valdés-González, Héctor; Reyes-Bozo, Lorenzo; Salazar, José Luis
This study investigates water consumption in two areas with limited water resources—the Salar de Atacama and Salar de Atacama-Vertiente Pacifico basins in Chile’s Antofagasta Region—with the aim of developing strategies that incorporate social and environmental aspects into water management. A qualitative approach was employed that involved a focus group with twelve water management representatives and surveys of the general population (468 responses). Additionally, the current state of water rights in the two basins was examined and the feasibility of the proposed strategies was assessed. The findings reveal that the mining industry’s development approach is mostly viewed as negative, mainly due to inadequate community engagement, confidential consumption data, and limited government oversight. The quantitative findings indicate that 53.8% of respondents see the main obstacle as the lack of a solution satisfying both parties. Additionally, 35.3%, 24.4%, and 22.4% believe transparency, objective information provision, and detailed resource usage disclosure by mining companies would help. Adopting a comprehensive water stewardship approach that considers social and environmental factors would enable a novel contribution to a more effective and sustainable water resource management system in northern Chile, mitigating communities’ negative perceptions of the industry and facilitating the integration of communities and involved agents. Therefore, improved management and transparent collaboration among stakeholders are essential for responsible water resource use in mining.
On a generalization of the Opial inequality
(2024) Bosch, Paul; Portilla, Ana; Rodriguez, Jose M.; Sigarreta, Jose M.
Inequalities are essential in pure and applied mathematics. In particular, Opial’s inequality and its generalizations have been playing an important role in the study of the existence and uniqueness of initial and boundary value problems. In this work, some new Opial-type inequalities are given and applied to generalized Riemann-Liouville-type integral operators.
Some new Milne-type inequalities
(2024) Bosch, Paul; Rodríguez, José M.; Sigarreta, José M.; Tourís, Eva
Inequalities play a main role in pure and applied mathematics. In this paper, we prove a generalization of Milne inequality for any measure space. The argument in the proof of this inequality allows us to obtain other Milne-type inequalities. Also, we improve the discrete version of Milne inequality, which holds for any positive value of the parameter p. Finally, we present a Milne-type inequality in the fractional context.
Inside the Black Box: Uncovering Dynamics and Characteristics of the Chilean Central Government Bureaucracy with a Novel Dataset
(2024) Brieba, Daniel; Herrera-Marín, Mauricio-René; Riffo, Marcelo; Garrido, Danilo
This article examines bureaucracies using a novel dataset of Chilean central government employees from 2006 to 2020. Unlike perception-based sources, this dataset provides objective, disaggregated, and longitudinal insights into bureaucrats’ characteristics and careers. The authors validate it against official employment statistics and conduct an exploratory and descriptive analysis, presenting six descriptive findings about the Chilean bureaucracy that cannot be discovered using available aggregate data. The analysis reveals significant degrees of personnel stability and professionalization in the civil service, but with considerable rigidity in careers and substantial interagency heterogeneity in turnover, wages, and exposure to political cycles. These findings suggest that the Chilean national bureaucracy is mostly well developed along Weberian lines, though not uniformly so. These measurements also serve as a benchmark for comparing other Latin American bureaucracies in the future.
On Shared Leadership Modeling: Contrasting Network and Dyadic Approaches
(2024) Coluccio, Giuliani; Muñoz-Herrera, Sebastián
Shared leadership is a dynamic phenomenon that has gained attention in behavioral science and management research over the last two decades. Network modeling is frequently employed to study this phenomenon, with the recent literature favoring a node-based approach over the traditional dyad-based approach. In this study, we investigate the differential impact of these approaches on shared leadership dynamics in student teams, specifically examining their effects on team task cohesion, team social cohesion, and team performance. We utilized multilevel structural equation modeling to compare node-based and dyad-based approaches in modeling shared leadership networks. Our findings indicate that increased leadership interactions positively influenced team performance and cohesion across both approaches. The dyad-based approach demonstrated a greater effect of leadership interactions on team performance, while leadership centrality significantly impacted performance exclusively in the node-based approach. This research contributes to the field by elucidating the differential impacts of node-based and dyad-based approaches, highlighting their strengths in capturing shared leadership dynamics and centrality effects. Our results underscore the critical importance of aligning theoretical foundations and research objectives with methodological choices in shared leadership studies. These insights enhance our understanding of shared leadership measurement and its implications for team outcomes, offering valuable guidance for future empirical investigations in this domain.
Long-term evaluation of commercial air quality sensors: an overview from the QUANT (Quantification of Utility of Atmospheric Network Technologies) study
(2024) Diez, Sebastian; Lacy, Stuart; Coe, Hugh; Urquiza, Josefina; Priestman, Max; Flynn, Michael; Marsden, Nicholas; Martin, Nicholas A.; Gillott, Stefan; Bannan, Thomas; Edwards, Pete M.
In times of growing concern about the impacts of air pollution across the globe, lower-cost sensor technology is giving the first steps in helping to enhance our understanding and ability to manage air quality issues, particularly in regions without established monitoring networks. While the benefits of greater spatial coverage and real-time measurements that these systems offer are evident, challenges still need to be addressed regarding sensor reliability and data quality. Given the limitations imposed by intellectual property, commercial implementations are often “black boxes”, which represents an extra challenge as it limits end users' understanding of the data production process. In this paper we present an overview of the QUANT (Quantification of Utility of Atmospheric Network Technologies) study, a comprehensive 3-year assessment across a range of urban environments in the United Kingdom, evaluating 43 sensor devices, including 119 gas sensors and 118 particulate matter (PM) sensors, from multiple companies. QUANT stands out as one of the most comprehensive studies of commercial air quality sensor systems carried out to date, encompassing a wide variety of companies in a single evaluation and including two generations of sensor technologies. Integrated into an extensive dataset open to the public, it was designed to provide a long-term evaluation of the precision, accuracy and stability of commercially available sensor systems. To attain a nuanced understanding of sensor performance, we have complemented commonly used single-value metrics (e.g. coefficient of determination, R2; root mean square error, RMSE; mean absolute error, MAE) with visual tools. These include regression plots, relative expanded uncertainty (REU) plots and target plots, enhancing our analysis beyond traditional metrics. This overview discusses the assessment methodology and key findings showcasing the significance of the study. While more comprehensive analyses are reserved for future detailed publications, the results shown here highlight the significant variation between systems, the incidence of corrections made by manufacturers, the effects of relocation to different environments and the long-term behaviour of the systems. Additionally, the importance of accounting for uncertainties associated with reference instruments in sensor evaluations is emphasised. Practical considerations in the application of these sensors in real-world scenarios are also discussed, and potential solutions to end-user data challenges are presented. Offering key information about the sensor systems' capabilities, the QUANT study will serve as a valuable resource for those seeking to implement commercial solutions as complementary tools to tackle air pollution.
QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation
(2024) Diez, Sebastian; Lacy, Stuart; Urquiza, Josefina; Edwards, Pete
the QUaNt study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. the resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors’ data and calibrated products from sensor manufacturers across the three sites. this publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset’s utility and reliability
The social stratification of internal migration and daily mobility during the COVID-19 pandemic
(2024) Elejalde, Erick; Ferres, Leo; Navarro, Víctor; Bravo, Loreto; Zagheni, Emilio
This study leverages mobile data for 5.4 million users to unveil the complex dynamics of daily mobility and longer-term relocations in and from Santiago, Chile, during the COVID-19 pandemic, focusing on socioeconomic differentials. We estimated a relative increase in daily mobility, in 2020, for lower-income compared to higher-income regions. In contrast, longer-term relocation rose primarily among higher-income groups. These shifts indicate nuanced responses to the pandemic across socioeconomic classes. Compared to 2017, economic factors in 2020 had a stronger influence on the decision to relocate and the selection of destinations, suggesting transformations in mobility behaviors. Contrary to previously held beliefs, there was no evidence supporting a preference for rural over urban destinations, despite the surge in emigration from Santiago during the pandemic. This study enhances our understanding of how varying socioeconomic conditions interact with mobility decisions during crises and provides insights for policymakers aiming to enact fair and evidence-based measures in rapidly changing circumstances.
The Role of River Vigilance Committees to Address New Socio-Climatic Conditions in Chile: Insights from Ostrom’s Design Principles for Common-Pool Resource Institutions
(2024) Julio, Natalia; Álvez, Amaya; Castillo, Rodrigo; Iglesias, Kimberly; Rivera, Diego; Ochoa, Fernando; Figueroa, Ricardo
Chile is currently facing a mega-drought, which is expected to lead to a significant increase in the water stress level. Social conflicts related to water use are linked to the effects of climate change and a governance system marked by the privatization of the natural resources of public interest. This study aims to analyze whether the current Chilean water governance scheme can adapt to the effects of climate change through a critical observation of the role of the River Vigilance Committees (RVCs; private user organizations exercising the public function of water management), from the perspective of Ostrom’s design principles for long-enduring Common-pool Resource (CPR) institutions. We analyze legal approaches, management mechanisms, and decision-making processes under the socio-climatic conditions that the country is currently facing. The results indicate that, with a few exceptions, the Chilean governance system does not allow RVCs to effectively incorporate the design principles—and, therefore, to achieve adaptation—due to dispersed functions, the exclusion of water users, and a lack of planning at different levels. We propose that water governance should consider the creation of River Basin Boards with broader planning powers, as well as the incorporation of different relevant stakeholders.
Decadal Variability of Dry Days in Central Chile
(2024) Latoja, Daniela; Lillo-Saavedra, Mario; Gonzalo-Martin, Consuelo; Godoy-Faúndez, Alex; Somos-Valenzuela, Marcelo; Rivera, Diego
Dry days are crucial in precipitation variability and water scarcity, particularly in Mediterranean regions facing increasing aridity. Despite their importance, most research focuses on precipitation amounts and temporal dynamics. This study addresses this gap by analyzing dry days’ temporal and spatial variability in central Chile (32–40 S), a region experiencing prolonged drought. We examined dry day patterns from 1960 to 2021 using high-resolution gridded precipitation data, defining dry days with five precipitation thresholds (0.10, 1, 2.5, 5, and 10 mm/day). Principal component and trend analyses were employed to characterize spatial and temporal variability. Results reveal a spatial pattern of dry days closely following precipitation patterns, with more dry days in northern and coastal areas. The first principal component explains 70–80% of the variance, and clustering methods allowed the definition of five homogeneous regions with distinct monthly dry-day characteristics. Long-term trends show a significant increase in annual dry days south of 38°S, while trends are weaker and non-significant further north. Notably, trend direction is highly sensitive to the analysis period, with some regions showing opposing trends before and after 1982. The 2010–2019 megadrought is detectable in decadal anomalies. We found links between dry day anomalies and large-scale climate patterns, suggesting modulation by changes in subtropical and extratropical atmospheric circulation. This comprehensive characterization of dry day climatology and variability provides crucial insights for water resource management and climate change adaptation in central Chile and similar Mediterranean regions worldwide. Our findings highlight the importance of considering dry day frequency in drought assessment and water planning, contributing to a more nuanced understanding of precipitation patterns in Mediterranean climates.
Explicit Modeling of Multi-Product Customer Orders in a Multi-Period Production Planning Model
(2024) Palma, Cristian D.; Vergara, Francisco P.; Muñoz-Herrera, Sebastián
In many industries, companies receive customer orders that include multiple products. To simplify the use of optimization models for planning purposes, these orders are broken down, and the quantities of each product are grouped with the same products from other orders to be completed in the same period. Consequently, traditional production planning models enforce minimum demand constraints by product and period rather than by individual orders. An important drawback of this aggregation procedure is that it requires a fixed order fulfillment period, potentially missing opportunities for more efficient resource use through early completion. This paper introduces a novel mathematical formulation that preserves the integrity of customer orders, allowing for early fulfillment when possible. We compare a traditional linear programming model with a new mixed-integer programming approach using a sawmill case study. Although more complex than the traditional model, the proposed formulation reduces costs by approximately 6% by enabling early order completion and offers greater flexibility and control over the production process. This approach leads to better resource utilization and more precise order management, presenting a valuable alternative to conventional production planning models.
Green hydrogen integration in aluminum recycling: Techno-economic analysis towards sustainability transition in the expanding aluminum market
(2024) Reyes-Bozo, Lorenzo; Fúnez-Guerra, Carlos; Salazar, José Luis; Vyhmeister, Eduardo; Valdés-González, Héctor; Jaén Caparrós, María; Clemente-Jul, Carmen; Carro-de Lorenzo, Francisco; Simón-Martín, Miguel de
The use of aluminum-based products is widespread and growing, particularly in industries such as automotive, food packaging, and construction. Obtaining aluminum is expensive and energy-intensive, making the recycling of existing products essential for economic and environmental viability. This work explores the potential of using green hydrogen as a replacement for natural gas in the smelting and refining furnaces in aluminum recycling facilities. The adoption of green hydrogen has the potential to curtail approximately 4.54 ktons/year of CO2 emissions, rendering it a sustainable and economically advantageous solution. The work evaluates the economic viability of a case study through assessing the Net Present Value (NPV) and the Internal Rate of Return (IRR). Furthermore, it is employed single- and multi-parameter sensitivity analyses to obtain insight on the most relevant conditions to achieve economic viability. Results demonstrate that integrating on-site green hydrogen generation yields a favorable NPV of 57,370, an IRR of 9.83%, and a 19.63-year payback period. The primary factors influencing NPV are the initial electricity consumption stack and the H2 price.
Assessing the effectiveness of static heuristics for scheduling lumber orders in the sawmilling production process
(2024) Vergara, Francisco P.; Palma, Cristian D.; Nelson, John D.
Although optimization models can be used to plan the production process, in most cases static heuristics, such as earliest due date (E), longest processing time (L), and shortest processing time (S), are used because of their simplicity. This study aims to analyze the production cost of the static heuristics and to determine how this cost relates to the size of the production orders in the sawmilling industry. We set a planning problem with different orders and due dates and solved it using two cost-minimization models to compare their solutions. The first was a planning model (PL) where orders were split up into products demand by period, and the second, a planning scheduling (PS) where the sequence of processing orders based on static heuristics was assumed as known. In the latter, the minimum production cost for each static heuristic was found. In both models, the same resource constraints were assumed. The costs showed no significant changes based on order sizes. However, 0,5 % of orders were delayed using PS-E, and 17 % of orders were delayed using PL. PL was an efficient solution method when changing the orders´ size and when looking for the best static heuristic to process the orders. However, PS-E showed the ability to reduce the backlog close to zero while the PL backlog ratio was 17 %. No penalties were applied to backlogs due to their subjective nature; however, when shortages occurred, the demand was unmet or backlogged with substantial costs. Thus, in case the proposed method is adopted using a conservative backlog cost, a sawmill producing under the cut-to-order environment that produces 300000 m3 /year would reduce backlogged orders by 51000 m3. If the holding lumber cost is 2 $/m3, annual savings would be $408000.
When another one bites the dust: Environmental impact of global copper demand on local communities in the Atacama mining hotspot as registered by tree rings
(2024) Zanetta-Colombo, Nicolás C.; Scharnweber, Tobias; Christie, Duncan A.; Manzano, Carlos A.; Blersch, Mario; Gayo, Eugenia M.; Muñoz, Ariel A.; Fleming, Zoë; Nüsser, Marcus
Assessing the impact of mining activity on the availability of environmental pollutants is crucial for informing health policies in anticipation of future production scenarios of critical minerals essential for the transition to a net-zero carbon society. However, temporal and spatial monitoring is often sparse, and measurements may not extend far enough back in time. In this study, we utilize variations of chemical elements contained in tree-rings collected in local villages from an area heavily affected by copper mining in the Atacama Desert since the early 20th century to evaluate the temporal distribution of pollutants and their relationship with local drivers. By combining time-varying data on local drivers, such as copper production and the dry tailings deposit area, we show how the surge in copper production during the 1990s, fueled by trade liberalization and increased international demand, led to a significant increment in the availability of metal(loid)s related to mining activities on indigenous lands. Our findings suggest that the environmental legislation in Chile may be underestimating the environmental impact of tailing dams in neighboring populations, affecting the well-being of Indigenous Peoples from the Atacama mining hotspot region. We argue that future changes in production rates driven by international demand could have negative repercussions on the environment and local communities. Therefore, mining emissions and the management of tailing dams should be carefully considered to anticipate their potential negative effects on human and ecosystem health.
Blowin’ in the Wind: Mapping the Dispersion of Metal(loid)s From Atacama Mining
(2024) Zanetta‐Colombo, Nicolás C.; Manzano, Carlos A.; Brombierstäudl, Dagmar; Fleming, Zoë; Gayo, Eugenia M.; Rubinos, David; Jerez, Oscar; Valdés, Jorge; Prieto, Manuel; Nüsser, Marcus
The Atacama Desert’s naturally elevated metal(loid)s pose a unique challenge for assessing the environmental impact of mining, particularly for indigenous communities residing in these areas. This study investigates how copper mining influences the dispersion of these elements in the wind-transportable fraction (<75 μm) of surface sediments across an 80 km radius. We employed a multi-pronged approach, utilizing spatial modeling to map element distributions, exponential decay analysis to quantify concentration decline with distance, regime shift modeling to identify dispersion pattern variations, and pollution assessment to evaluate impact. Our results reveal significant mining-driven increases in surface concentrations of copper (Cu), molybdenum (Mo), and arsenic (As). Notably, within the first 20 km, concentrations peaked at 1,016 mg kg⁻1 for Cu, 31 mg kg⁻1 for Mo, and a remarkable 165 mg kg⁻1 for As. Cu and Mo displayed significant dispersion, extending up to 50 km from the source. However, As exhibited the most extensive reach, traveling up to 70 km downwind, highlighting the far-reaching ecological footprint of mining operations. Mineralogical analyses corroborated these findings, identifying mining-related minerals in surface sediments far beyond the immediate mining area. Although pollution indices based on the proposed Local Geochemical Background reveal significant contamination across the study area, establishing accurate pre-industrial baseline values is essential for a more reliable assessment. This study challenges the concept of “natural pollution” by demonstrating that human activities exacerbate baseline metal(loid)s levels. Expanding monitoring protocols is imperative to comprehensively assess the combined effects of multiple emission sources, including mining and natural processes, in safeguarding environmental and human health for future generations.
The impact of electromobility in public transport: An estimation of energy consumption using disaggregated data in Santiago, Chile
(2024) Basso, Franco; Feijoo, Felipe; Pezoa, Raúl; Varas, Mauricio; Vidal, Brian
Electromobility in public transport has become a promising way to reduce environmental pollution. Several contributions have sought to estimate the energy consumption of buses in public transport. However, most of these efforts use measurements collected from controlled or simulated experiments, or that do not characterize the entire bus network. Unlike these studies, this article estimates the energy consumption of all the electric buses that circulate in the city of Santiago, Chile, during the studied period using full disaggregated GPS data and empirical measurements on some sensorized electric buses. The methodology considers a feature selection phase and the development of energy consumption prediction models using physics based and machine learning approaches. The performances of both models are compared with each other, and then, the best one is used to measure the impact of electromobility in the city. This analysis allows decision-makers to target investment by determining the buses with higher energy consumption savings in the face of budget constraints.
The impact of lockdown, fatigue, and social interaction on highway demand during the COVID-19 pandemic: The case of Santiago, Chile
(2024) Basso, Franco; Batarce, Marco; Pezoa, Raúl; Villalobos, Matías; Varas, Mauricio
The COVID-19 pandemic, as well as the government measures to curb its spread, have significantly affected mobility. Various studies have investigated behavioral changes across different transport modes accounting for sociodemographic variables, yet the focus has predominantly been on public transportation. This article addresses this gap by quantifying the impact of mobility restrictions on an urban highway in Santiago, Chile. To do so, we develop several econometric models based on panel data, which enable us to assess control measures’ effects while accounting for their spatial heterogeneity. Our computational experiments demonstrate that traffic reductions were more significant among higher-income drivers (1% reduction per each 100,000 pesos increase). Conversely, municipalities with a higher proportion of elderly residents saw less drastic decreases in traffic. Regarding the effectiveness of control measures, we confirm that the lockdown is affected by fatigue and social interaction. The fatigue implies that users do not fulfill the lockdown as time passes, reducing the effect of quarantines by about 50% during October, 2020. The social interaction effect suggests the lockdown is less effective when not all city’s municipalities are restricted to travel, which might be an argument against dynamic or partial lockdowns.

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