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This paper shows an agricultural irrigation alternative using a low-cost Internet of Things (IoT) application. This technology allows the automation and optimization of processes by monitoring, processing, and analyzing large volumes of related data, including variables related to the soil (moisture), fertilization, and irrigation, which can be visualized through the internet to enable sustainable and efficient agriculture. The study is centered on the Los Angeles, Biobío, Chile case. The main objective of the prototype is to optimize water consumption for agricultural irrigation by using only the amount that is strictly necessary for each crop by allowing real-time visualization of irrigation status, moisture data, and irrigation times while providing a history of data that can be used for further analysis. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative approach towards real-time earthquake forecasting in Chile by integrating intelligent technologies and machine learning methods. Earthquakes pose significant risks to communities and infrastructure in Chile, making accurate and timely forecasting crucial for disaster preparedness and mitigation. Traditional forecasting methods have limitations in providing real-time insights into seismic activity. In contrast, intelligent technologies such as artificial intelligence (AI) and machine learning offer promising avenues for enhancing prediction accuracy and speed. A new earthquake forecasting method using a modified clustering approach LMSCAN(Local Maxima-based Spatio-Cluster Analysis Network) and enhanced neural network time series analysis LSTM-IC (Long Short Term Memory Inverse Correlation) is presented in this paper. This neural network-based technology has been utilized to forecast earthquakes in the Chile region, one of the countries with the largest seismic activity. This study explores the integration of intelligent systems with machine learning algorithms to analyze seismic data and predict earthquake occurrences in Chile. By leveraging historical seismic data, sensor networks, and advanced predictive models, our approach aims to provide timely warnings and insights into seismic events, thereby improving disaster response and resilience. The proposed framework holds the potential to revolutionize earthquake forecasting by enabling real-time monitoring and proactive measures to safeguard communities and infrastructure in Chile and beyond. The remarkable 95 % accuracy achieved by this model is a testament to its exceptional learning process, which sets it apart from other models. Its ability to learn and adapt to new data is unparalleled, allowing it to forecast incredibly precisely and produce highly reliable results. [ABSTRACT FROM AUTHOR]

Changing environmental data analytics modify perceptions and policies on resources, particularly in terms on mining legitimisations. Enhanced data products are critical for improved planning and execution of extractive activities. Improved data in the mining industry tends to increase definitions and scale levels thus segregating environmental features from each other. This tends to be in conflict with local contingent appreciations of resources and their interactions with broader environmental features and conditions. Data scales and availabilities influence which resource perception dominates and so how mining is justified or antagonised successfully. This paper contributes to discussions that explore resource materialities from analyses of lithium mining. It focuses on the Atacama Salt Flat in contexts of lithium mining and material metrics, and separates itself from focuses on global availability of reserves by taking a narrower discussion on chemical differences that contour abundancy, variety and rarity of materials. This paper is based on fieldwork conducted in 2019 in Chile. It presents the current state of social appreciations on lithium materialities in and around places of extraction in Chile. Centrally, it unpacks an analysis of the social values of lithium and sets grounds for thinking about how a social value of a material becomes prevalent over other social values, particularly in contexts of global material needs and local environmental change for climate change mitigation solutions. • Affordances of data products on the Atacama Salt Flat sustain social values that favour lithium extraction. • Legitimisations to extract materials in the global south benefit from data products that increase metrics and categories of materials. • Contestations to lithium mining in San Pedro de Atacama use dominant discourses that better sustain extraction. • Environmental policy-making need to scrutinise data products from the outset of social values. • Data-driven responsible material sourcing should integrate social value assessments • There is no clear-cut definition of social value respective to the environment and progress on its understanding is context and place specific. [ABSTRACT FROM AUTHOR]

Supply schemes, specifically delivery times, are essential factors in the resulting final cost of fuels. It is the particular case of hydrogen produced from variable renewable energies. However, the impact of different delivery times on the levelized cost of hydrogen (LCOH) remains unclear. This paper assesses the combined impact of different delivery times, local renewable sources, and onsite generation curtailment on the LCOH. We developed an optimization model of an electrolysis-based hydrogen plant and found key LCOH locational drivers and trends. The model uses hourly solar PV and wind generation data for four locations in Chile and optimizes the capacities of the onsite solar and wind generators, electrolyzers, storage tanks, and compressors. In all the locations examined, we found an almost linear relationship between LCOH and delivery time. LCOH values for a daily delivery range from 2.4 to 3.4 $US/kg (for different locations). Values for a delivery time of 120 days range from 12.2 to 13.6 $US/kg. These are explained by the almost linear increase in storage costs with respect to delivery time, despite the variability of renewable energies at the analyzed locations. Production costs remain almost constant for different delivery times. Furthermore, we obtained that curtailment could decrease LCOHs between 5% and 40%, by increasing the electrolyzer's capacity factor and decreasing the storage size. Moreover, we show that off-grid solar-dominant scenarios are strongly affected by the lack of solar energy in winter, increasing LCOHs considerably. • Linear relationship between LCOH and delivery time. • Low delivery times imply less volume and cost of storage, decreasing the LCOH. • Production costs remain almost constant for different delivery times. • Curtailment reduces LCOHs between 5% and 40% due to increased capacity factors. • Off-grid solar dominant locations present higher LCOHs due to winter's lower solar generation. [ABSTRACT FROM AUTHOR]

This paper uses rich administrative data from Chile to estimate teacher value added (TVA) on test scores and on an educational attainment index. We allow each teacher to have a different TVA for male and female students and show that differences in TVA explain an important part of the gender gaps we observe in test scores and postsecondary education trajectories. The gaps in gender-specific teaching effectiveness are especially pronounced in mathematics. Indeed, eliminating within-teacher differences in math test score VA would reduce the gender gap in math performance by 67%. We explore what could be behind these gaps in gender-specific TVA and find no significant differences in what makes teachers effective for male and female students. We do find, however, significant associations between teacher characteristics—e.g., gender and performance in the college admission exam—and practices—e.g., paying attention to low-performing students, congratulating students who improve, and having a good relationship with students—with teacher effectiveness. Finally, we also show that math teachers tend to be biased in favor of male students and that teachers with smaller gender biases are more effective for both, male and female students. [ABSTRACT FROM AUTHOR]

The following study explores how the preservation of the sense of community through collaborative mechanisms and the strengthening of a Smart city governance reduce the vulnerability of cities. Chiloé archipelago is selected as the case to study, given its vernacular architecture, in relation to wood, geography, cultural enrichment associated with tourism and a consolidated and integrated governance model for its population. The paper reviews secondary sources and build an urban management model, applied to the case, to conclude that preserving the sense of community and strengthening Smart city governance, reduces the vulnerability of cities in a sustainable approach. [ABSTRACT FROM AUTHOR]

Water scarcity is a critical issue worldwide and has become a major constraint on socio-economic development. Seawater desalination is an appealing adaptation option in regions with access to the coast; however, it has sustainability challenges that require careful consideration. Two critical challenges are: how to manage the spectrum of potential adverse social and environmental impacts; and how to provide fair and sustainable water access benefits to the region as a whole. This paper presents a participatory modelling framework designed to support the participatory planning of sustainable integration of desalinated seawater into a regional water supply network in water-scarce regions. The framework is based on a modelling tool that facilitates collaborative understanding of the regional context and optimises and maps candidate water supply networks and the associated trade-offs between economic, environmental and social performance criteria. The framework aims to facilitate dialogue between all interested parties and contributes to a more informed, fair, consented, long-term and sustainable integration of desalinated seawater into regional water supply schemes. An application to the Atacama region in Chile illustrates the capabilities of the framework to communicate options under varying conditions of environmental protection. The case study also illustrates the role of stakeholders in the process of tool refinement as part of early-stage participatory planning. • Water supply planning framework to support participatory planning. • Supports fair and sustainable integration of desalination in regional water supply. • It encompasses both spatial layout and network optimisation planning. • It incorporates environmental, social and economic aspects in planning stages. • The Atacama region (Chile) application illustrates trade-offs of shared solutions. [ABSTRACT FROM AUTHOR]

Committed to achieving carbon neutrality by mid-century, South America faces unique challenges in carbon mitigation due to its distinct socio-economic, technological, and institutional backgrounds compared to developed and other developing economies. Previous research on South America's carbon emissions has limited country and sector coverage and typically adopts a top-down approach that focuses on the overall emissions of an economy, neglecting individual energy sources and emission sectors. Therefore, this paper compiles a comprehensive inventory of CO 2 emissions for South American countries based on a meticulous bottom-up approach and multi-source data integration, followed by a thorough analysis of their temporal evolution patterns and the driving forces behind them. Between 2010 and 2020, South America's overall emissions peaked in 2014 at 1092.3 Mt., led by emissions from oil consumption and from the transport and electricity sectors, and dropped to 865.6 Mt. in 2020, due to the economic fluctuations and COVID-19. Specifically, Brazil was the largest emitter, Chile experienced the most significant increase in emissions, and Paraguay recorded the highest emission growth rate. Generally, expanding population was constant driver of emission growth. High energy intensity led to significant emission increases in Brazil and Ecuador, while elevated carbon intensity was the main driver in Argentina. Energy structure changes played a positive role in most countries to different extents (e.g., much more significant in Brazil than in Chile) but aggrevated emissions in Paraguay and Guyana. Therefore, carbon mitigation strategies should be tailored to each country's unique national circumstances. • During 2010–2020, South America's CO 2 emissions from fossil fuels peaked in 2014. • Transport and electricity sectors comprised over 60% of total emissions. • Brazil was the top emitter, while Chile saw the largest increase in emissions. • Emission patterns and driving factors varied significantly across countries. • Carbon reduction strategies should be tailored to local circumstances. [ABSTRACT FROM AUTHOR]

The occurrence of contaminants of emerging concern (CECs) in environmental systems is gradually more studied worldwide. However, in Latin America, the presence of contaminants of emerging concern, together with their environmental and toxicological impacts, has recently been gaining wide interest in the scientific community. This paper presents a critical review about the source, fate, and occurrence of distinct emerging contaminants reported during the last two decades in various countries of Latin America. In recent years, Brazil, Chile, and Colombia are the main countries that have conducted research on the presence of these pollutants in biological and aquatic compartments. Data gathered indicated that pharmaceuticals, pesticides, and personal care products are the most assessed CECs in Latin America, being the most common compounds the followings: atrazine, acenaphthene, caffeine, carbamazepine, ciprofloxacin, diclofenac, diuron, estrone, losartan, sulfamethoxazole, and trimethoprim. Most common analytical methodologies for identifying these compounds were HPLC and GC coupled with mass spectrometry with the potential to characterize and quantify complex substances in the environment at low concentrations. Most CECs' monitoring and detection were observed near to urban areas which confirm the out-of-date wastewater treatment plants and sanitization infrastructures limiting the removal of these pollutants. Therefore, the implementation of tertiary treatment should be required. In this tenor, this review also summarizes some studies of CECs removal using electrochemical advanced oxidation processes that showed satisfactory performance. Finally, challenges, recommendations, and future perspectives are discussed. [Display omitted] • Occurrence of contaminants of emerging concern (CECs) in Latin America. • Pharmaceuticals, pesticides and personal care products are the most assessed CECs. • The presence of CECs were predominantly observed in close proximity to urban areas. • Electrochemical technologies are an important alternative for CECs elimination. [ABSTRACT FROM AUTHOR]

This paper presents a case study on power control and energy management for a 60 apartments' residential building with solar generation and energy storage tied to the grid in Santiago, Chile. A new energy management algorithm based on energy homeostasis is designed for a small electro thermal generation system (nanogrid), with smart metering. The test bed employs supervisory control with energy management that regulates the temperature inside a large room by the action of an HVAC (Heating/Ventilating/Air Conditioning) unit. The main objective of supervisory control is to allow temperature comfort for residents while evaluating the decrease in energy cost. The study considers a room with rooftop grid-tie nanogrid with a photovoltaic and wind turbine generation plant, working in parallel. It also has an external weather station that allows predictive analysis and control of the temperature inside the abode. The electrical system can be disconnected from the local network, working independently (islanding) and with voltage regulation executed by the photovoltaic generation system. Additionally, the system has a battery bank that allows the energy management by means of the supervisory control system. Under this scenario, a set of coordination and supervisory control strategies, adapted for the needs defined in the energy management program and considering the infrastructure conditions of the network and the abode, are applied with the aim of efficiently managing the supply and consumption of energy, considering Electricity Distribution Net Billing Laws 20.571 and 21.118 in Chile (https://www.bcn.cl/historiadelaley/historia-de-la-ley/vista-expandida/7596/), the electricity tariffs established by the distribution company and the option of incorporating an energy storage system and temperature control inside the room. The results show the advantage of the proposed tariffs and the overall energy homeostasis management strategy for the integration of distributed power generation and distribution within the smart grid transformation agenda in Chile. [ABSTRACT FROM AUTHOR]

• Experimental study on multi-layer strong wood shear walls. • Influence of nonstructural Type X GWB finishes on the lateral response of strong wood shear walls. • Significant increase in strength and stiffness, no significant reduction of the deformation capacity. • Calibration of the parameters of the SDPWS model. • A numerical model that accounts for different types of connections acting as a system was found reasonably accurate. A fundamental premise for the design of resilient light frame timber buildings in areas of high seismic activity consists of achieving strong shear walls while keeping nonstructural damage to a minimum, especially by preventing the brittle failure of Type X gypsum wallboard (GWB) finish layers. Under this premise, it has been commonly thought that the stronger the shear wall the lesser the structural contribution of the finishes, and therefore the effect of GWB finishes in strong timber shear walls has been typically ignored by design codes and mechanical models. In the research reported in this paper, the influence of nonstructural finishes on the structural characteristics of a strong light frame shear wall was experimentally and numerically investigated. The wall evaluated in this paper, denoted here Multi-Layered Strong Shear Wall (MLSSW), is representative of walls located at the 1st story of a 7-story building located in Chile, a country where the level of seismic activity is high. The MLSSW has a continuous rod system, double OSB sheathing, robust timber framing, closely spaced nails to attach the OSB sheathing layers to wood-frame members, and is covered at both sides by two layers of screwed Type X GWB. The characteristics of the MLSSW, particularly the quantity and type of nonstructural finishes, are different from those of typical light frame timber walls. Full-scale connection-level tests, both monotonic and cyclic, are reported first, followed by descriptions of the full-scale cyclic assembly-level tests. For comparison purposes, a bare strong wall (i.e., without the GWB layers) was tested as well. The structural response of the MLSSW was evaluated in terms of stiffness, strength, energy dissipation and plastic deformation characteristics. The applicability of the SDPWS analytical model was also evaluated, as well as the applicability of existing numerical models to predict the cyclic behavior of the MLSSW. [ABSTRACT FROM AUTHOR]

This paper investigates the causal effect of COVID-19 quarantine measures on the electricity consumption of different types of regulated customers. In particular, the average energy consumption of a group of customers in Chile is examined, exploiting the weekly variations in the application of the stages of the Step by Step Plan as a natural experiment. Step by Step Plan was the Chile COVID containment strategy, which involved implementing partial lockdowns based on the COVID incidence in the municipalities, and adjusted on a weekly basis. An econometric model is specified, and estimated using the technique Difference-in-Difference-in-Difference (DDD) to quantify the causal impact of these measures. After applying the model, it is found that the quarantine measures have had a negative effect on the trend weekly consumption of customers located in municipalities where some of the phases of the Plan have been applied. This effect is significantly different depending on each stage of the plan analysis, and statistically significant. It is also observed that, on average, the savings for a representative customer in the sample range from $ 8 to $ 6. 15 for some municipalities, and the sample costs range from $ 0. 02 to $ 0. 26 for others, depending on the municipality analyzed. The results can be expressed in a total of 2.95 tons less CO 2 emitted on a monthly basis. This shows a great impact in terms of sustainability and planning of energy demand and supply. • Quarantines by Covid 19 affected energy consumption, like a "Natural Experiment". • Using Panel Data of 400 thousand observations with geographic, temporal and Daylight Saving Time controls. • Difference-in-Difference-in-Difference method to quantify causal impact of quarantines on electric consumption. • Applying quarantines generated Energetic Savings from 8 cents to 6.15 dollars depending on client type. • An Event Study was designed to check the estimation results. [ABSTRACT FROM AUTHOR]

Microgrids (MGs) are sustainable solutions for rural zone electrification that use local renewable resources. However, only careful planning at the start of an MG project can ensure its future optimal operation. In this paper, a novel methodology for MG planning by using the uncertainty characterization of renewable resources and demand is presented. Additionally, a model of electricity consumption is proposed and applied in an isolated rural community. In such communities, consumption patterns typically need to be derived as model inputs because consumption measurements are not available for the planning stage. To obtain these inputs, clustering algorithms based on self-organizing maps (SOMs) and fuzzy c-means are used to classify the families of the community given sociodemographic information obtained via surveys. Subsequently, Markov chains (MCs) are employed to generate consumption patterns based on consumption measurements in some dwellings and surveys applied to the community. The nonlinearities and uncertainties associated with renewable resources and consumption are modeled by using prediction interval (PI) models. These PI models provide the required consumption and generation scenarios for deriving the optimal sizing and topological information to address the MG planning problem. The results of the robust planning approach based on scenarios are useful at the feasibility and design phases of an MG project. The proposed methodology is successfully applied to MG planning for a rural Mapuche community, where a conservative criterion was considered to minimize the investment risk. This criterion corresponds to the worst-case scenario in which the demand increases by 19.9% compared to that of the baseline scenario and a lower energy cost is obtained. However, the net present cost and operational costs increase by 14% and 11.75% compared to those of the baseline scenario, respectively. • Clustering algorithms and Markov chains are used to generate consumption patterns. • Prediction interval models contribute to generating scenarios for MG planning. • The proposed methodology is validated in a rural Mapuche community in Chile. [ABSTRACT FROM AUTHOR]

Value generation occurs during the life cycle of construction projects. However, the ability to influence the projects' characteristics at the design stage increases the probability of maximizing value. Nevertheless, few studies assess value creation during the design. Considering this gap, the aim of this paper is to analyze the value generated at the design stage of Chilean construction projects. The research method responds to a descriptive type of study consisting of three stages: design value attributes definition, assessment and quantitative measurement of value applying a Value Analysis Model recently developed, and value comparison. Twenty-eight value attributes were selected from literature review and grouped into seven satisfaction conditions. The value assessment was performed through a questionnaire applied to 47 Chilean companies within the construction industry. The main findings show that 1) companies, in general, have low-value expectations related to the design process and, in turn, low-value generation, which can be negatives values; 2) projects tend to compensate the lack of indispensable attributes with the inclusion of attractive features, thereby demonstrating an absence of prioritization; and 3) the satisfaction conditions with the highest value generation are business environment, schedule and budget, and with lowest value generated are deliverables, integration and tools and technology. The primary contribution of this study is be useful to designers, managers and researchers, as it provides information on focus attributtes that require appropriate care to improve value within design-build processes; and for any project or company wanting to know its value benchmarking concerning other projects. [ABSTRACT FROM AUTHOR]

• Losses of stiffer buildings resulted higher because of their higher seismic hazard. • Losses for the studied buildings are less than estimated for RC frame buildings. • Losses are mainly due to the cases of non-collapse. • Repair costs of partitions contributed the most to the total loss of the buildings. This research paper evaluates the effect of lateral stiffness on expected economic losses in reinforced concrete shear wall buildings designed following current Chilean standards, including DS60 and DS61. Economic losses were evaluated for a group of four 20-story archetype buildings located in Santiago, Chile. The methodology developed by the Pacific Earthquake Engineering Research Center was considered to estimate economic losses. The expected annual loss (EAL) and the present value (PV) of the losses in 50 years were used as measures of economic loss. A probabilistic seismic hazard analysis, which considered the seismicity of central Chile, was performed to estimate both metrics. The results show that when the lateral stiffness of the building increases, the EAL also increases. This implies that stiffer buildings are more vulnerable from an economic point of view. This counter-intuitive finding results from the higher seismic hazard of stiffer buildings and the minimum design base shear required by DS61 that governed the design of the studied buildings. Additionally, it was found that the EAL and the PV of losses in 50 years for the four archetypes do not exceed 0.3% and 7.8% of the total construction cost of the buildings, respectively. These monetary losses are relatively low, which is consistent with the outstanding seismic performance of reinforced concrete shear wall buildings. [ABSTRACT FROM AUTHOR]

Developing countries tend to suffer the most from natural disasters, but the mechanisms underlying this outcome are poorly understood. In this paper, I study one of the potential mechanisms behind this pattern: the lack of strong and well-defined property rights for renewable resources. Using fisheries as an example, I examine how different property rights regimes dictating who has access to the resource could determine the overall exposure, as well as the cost of the rebuilding paths that fishers follow after a natural disaster. Using small-scale fisheries in Chile as a case study, I show that fisheries operating in common access are on average more exposed and also follow costlier recovery paths after the tsunami that hit the country in 2010. This paper contributes to the ongoing work on the economic impact of natural disasters and provides an argument for further study of how institutional regimes can be also understood as potential adaptation strategies. [ABSTRACT FROM AUTHOR]

The regional impact of climate change on heating and cooling demand is important to consider when designing optimal long-term energy policies. Several studies have addressed this issue, but either at a very aggregated level or without optimizing the whole energy system. The aims of this paper are to fill this gap in a generic way and to assess the impact of climate change on heating and cooling energy demands for residential and commercial sectors at the regional and nodal levels in the context of Chile's energy transition. We propose a methodology based on high resolution climate simulations for the Representative Concentration Pathways (RCP) RCP 2.6 and RCP 8.5 scenarios. First, a statistical analysis is performed to estimate the long-term trends of so-called heating and cooling degree-days and their impact on final regional energy demands. Then, demand pathways in the energy transition are assessed using a multi-sectoral energy planning model. Numerical experiments using data from Chile show an overall positive economic impact of climate change (limited to heating and cooling demands) for the energy system, with a significant decrease in heating demand compared to a limited increase in cooling requirements. For the RCP 8.5 scenario, cost reductions reach 2.1% of the total discounted system cost on the 2020-2050 period mainly due to a significant decrease of gas consumption for heating. This research highlights the importance for policymakers to consider climate change in efficient energy policies. [Display omitted] • Climate change impact on heating/cooling is assessed for Chile's energy transition. • Significant heating demand decrease and low cooling demand increase are observed. • A global positive economic impact for the energy system is estimated. • For the RCP 8.5 scenario, cost reductions reach 2.1% of the total discounted system cost. [ABSTRACT FROM AUTHOR]

In this paper, machine learning models are used to improve a wave hindcast database created using WAVEWATCH III® (WW3) for the Chilean coast. The models were trained with 50,505 data entries from two buoys and eleven ADCPs. The machine learning models significantly improved the results from WW3 for three parameters: significant wave height, mean wave period, and mean wave direction. Our best performing model, which is based on a convolutional neural network and uses the directional wave spectrum as input, reduced root mean squared errors in the significant wave height by 71%, peak wave period by 61% and mean wave direction by 63%. Most importantly, our method dramatically improved the mean wave direction in four locations where WW3 was particularly problematic (absolute error reduction of 20°). The neural network corrections can also be applied to other locations if sea states conditions are similar to the training data. The research presented here show that machine learning techniques are a fast and effective way to improve existing wave hindcast databases at relatively low cost. • Three machine learning models were tested to improve a wave hindcast database created using WAVEWATCH III® for the Chilean coast. • The models were trained with 50,505 data entries from two buoys and eleven ADCPs along the central south of Chile. • Our best performing model reduced RMSE: 71% in significant wave height, 61% in peak wave period and 63% in mean wave direction when considering test data only. • The neural network corrections can also be applied to other locations without increasing the errors in nodes that already had good agreement between WAVEWATCH III® and the observed data. [ABSTRACT FROM AUTHOR]

Hydrogen (H 2) can be a critical factor in achieving a more sustainable society reducing carbon emissions worldwide in the long run. However, there are some challenges to be solved yet. One of these challenges is that, right now, the economical competitiveness of electrolysis production strongly depends on the Renewable Energy Sources (RES) availability. This paper analyzes the economic and environmental implications of complementing the power supply of a H 2 production plant that usually operates using only RES with grid electricity during the time RES are not available. For performing this analysis, we proposed an assessment model that incorporates Alkaline (ALK) and PEM electrolyzer technology features (such as the low dynamic load range of ALK electrolyzers, which is usually ignored when modeling H 2 production). Moreover, we introduce a new metric, named the LCOH&E, which captures the existing trade-off between reducing the Levelized Cost Of Hydrogen (LCOH) with more H 2 production using grid electricity and increasing CO 2 emissions by producing more H 2 with grid electricity. We illustrate the proposed assessment model with a case study based on real data from Chile. Our results show that the optimal fraction of grid electricity to be used in producing H 2 may be different when minimizing the LCOH and when minimizing the LCOH&E because of the LCOH-CO 2 emissions' trade off. Moreover, it is remarkable that using only 10% of grid electricity in an ALK electrolyzer, it is possible to increase the H 2 production in 25.7%, without significantly increasing the CO 2 emission level. • This paper analyzes the value of adding grid electricity to a pure RES H 2 production plant. • The Levelized Cost of Hydrogen and CO 2 emissions are obtained for Alkaline and PEM electrolyzers. • We combine the Levelized Cost of H 2 and the CO 2 emissions in a single cost function to optimize. • The assessment model incorporates crucial ALK and PEM technology features of the H 2 production. • Using only 10% of grid electricity in an ALK electrolyzer, H 2 production can increase 25.7%. [ABSTRACT FROM AUTHOR]

This paper discusses the design and deployment of low-cost Internet of Things (IoT) in medium-scale open pit mines to optimise the performance of their mining small-scale trucks and surface mining shovels. Low-cost IoT can be implemented in medium-scale operations to automate the collection of process management information that is currently measured manually, replicating part of the results delivered by commercial Fleet Management Systems (FMSs) such as the calculations of the number of truck cycles per shift, the shovel loading time, truck and shovel positioning, tonnes moved per day, truck speed and average fleet efficiency. The process of developing mining benches can also be monitored. By monitoring these tasks, FMSs in the mining industry allow mine operators to maximise productivity, reduce the number of equipment required to accomplish production targets, minimise material re-handling, supply the plant as planned and meet ore blending objectives for better metallurgical recoveries. In the case of large-scale mines, these mining operations are prepared to invest in the high cost of a typical FMS (of the order of $100,000/month depending on fleet size) because they enable mine operators to ensure that their capital-intensive fleets operate at peak productivity, generating maximum return on investment. By contrast, many medium-scale mines cannot afford the installation and ongoing costs associated with a commercial FMS. Medium-scale mines typically have low capitalization, rented mining fleet and are run on a day-to-day basis, with staff being employed or laid off on an almost continuous basis. The emergence of low-cost IoT promises widespread and access to sensors and data that can be used for operational decision-making. This paper presents a trial of a low-cost, under $100, IoT-based Fleet Information System (FIS). The system does not attempt to replicate the functionality of a full FMS but delivers key management information to the mine operators while having low capital and running costs and no requirement for IT or technical skills for installation or maintenance. In a test case in Chile, the FIS was used to inform operational management changes that resulted in a reduction of loading time, optimisation of mining truck routes and truck speed control for better safety without an increase in the mining cost. The low cost of the solution allows medium-scale mines access to tools that can enable them to mirror the performance improvements of their bigger competitors. For medium-scale mines, that means longer life-of-mine, more local employment and a longer positive impact in the community. • A US$100 per unit Fleet Information System (FIS) has been designed for truck and shovel operations on medium-scale mines. • The FIS automates the collection of management information that is currently measured manually at medium-scale mines. • Results delivered by commercial Fleet Management Systems can be replicated with potential to deliver lower running costs. • The system developed in this paper is deliberately designed without an interface in the cabins of the trucks or shovels. • Hardware knowledge is not required to install the system and the system does not require on-site IT expertise. [ABSTRACT FROM AUTHOR]

Carbon taxes have been proposed as a major instrument to mitigate carbon emissions and promote an energy transition to low carbon sources. However, its adoption remains politically challenging, particularly amid rising inflation and energy prices. Despite the need for more aggressive action on carbon mitigation to reach the Paris Agreement goals, few countries in Latin America have adopted carbon taxes and the tax levels are relatively low. A key concern for these countries, is to adequately assess the tradeoffs between stricter emission goals and the potential negative economy wide as well as sectoral and distributive impacts. In this context, in this paper we first propose a step by step approach to enhance an existing dynamic Computable General Equilibrium (CGE) model for Chile based on OECD's Green model. The contribution of this research is twofold. Firstly, emission factors are estimated and the development of the electricity sector is aligned with the expectations of decision makers. As a result, credible emission and energy sector development forecasts are generated by the model, that are in line with what policymakers expect to happen based on other bottom-up engineering models. Secondly, this baseline is then used in the CGE model to examine the use of a carbon tax to reach Chile's first Nationally Determined Contribution. The required tax level is determined together with CO2 emissions and the economywide, sectoral and distributive impacts. The results allow concluding about the applicability of carbon taxes and possible complementary measures. [ABSTRACT FROM AUTHOR]

In this paper, we retrace the geomorphological evolution of a 6.5 km-long segment of the Blanco Este River, which drains the Calbuco volcano in southern Chile, highlighting the geomorphic signatures of the disturbances caused by the 1961 and 2015 eruptions. In particular, we track the geomorphological changes and the evolution of the geomorphological units and discuss the underlying processes. In addition, we use the NDVI (Normalize Difference Vegetation Index) to characterise the vegetation recovery at the basin and the active channel scales. The reconstruction of the geomorphological changes is performed by means of photointerpretation and supervised classification image analysis. Moreover, we quantify braiding indices and active channel widths to characterise the fluvial corridor and to describe its evolution after the two eruptive events. It is found that the evolutionary trajectories of the Blanco River immediately after the eruptive events of 1961 and 2015 exhibited strong similarities. In fact, the major geomorphological adjustment of the Blanco Este River occurred during the first period of observation (19 years) after the 1961 eruption. Subsequently the river progressed gradually towards an advanced relaxation stage in 2014. For 53 years (between 1961 and 2014), the reduction of the active channel width was the dominant process, followed by erosion, which favoured the regeneration and consequent expansion of vegetation cover within the river corridor. The 2015 eruption reset the fluvial landform and a new cycle of sedimentation, braiding and formation of central bars began; the highly dynamic pattern is still observed today. [ABSTRACT FROM AUTHOR]

Implementing nationally determined contributions is more challenging for developing countries given potential economic consequences. Chile, a developing economy, is committed to reaching carbon neutrality by 2050. To do so, Chile announced multiple mitigation strategies such as phasing out coal by 2040, peaking emissions by 2025, and developing renewable energies. Fortunately, Chile holds a prominent renewable potential, standing out for solar, but it also has a significant challenge decarbonizing an economy that heavily relies on fossil fuels. The contribution of this paper is twofold. First, the first country-level disaggregated version of GCAM Latin America (GCAM-LA) was developed, where all South American countries are modeled as an independent energy-economy region. This model includes Chile as a separated region and incorporates interactions among the energy, water, agriculture and land use, economy, and climate systems. Second, different decarbonization strategies to reach carbon neutrality by 2050 were obtained, considering technology availability and high renewable energy potential. Results indicate that carbon neutrality is feasible when enforcing different combinations of the current Chilean mitigation strategies, even delaying coal phase-out by five years and failure of developing advanced solar technologies. If some policies are not fully implemented, such as delaying coal phase-out by five years or failure of developing advanced solar technologies, carbon neutrality can be achieved by incurring in a higher capital cost in the power sector. Moreover, decarbonization is mainly driven by high electrification levels in the final demand sector, reaching 53.7%–62.9% of the total consumption. However, such levels of electrification are reduced, particularly in the transport sector, when Chile relies on negative emissions from the land use and forestry sector. [ABSTRACT FROM AUTHOR]

The discontinuities are main factor on discontinuous, anisotropic, and non-elastic behavior of rock mass. The objective of this paper is to present a new discontinuity rating system called "Universal Discontinuity index" (UDi), based on the combination of quantitative and measurable parameters of the discontinuity network, damage mechanics, vectorial based criteria of Warburton for kinematic rock block failure analysis, and Mohr-Columb criteria for shear failure analysis. Applying the UDi permits to capture the heterogeneous and anisotropic nature of the rock mass strength or equivalently the degree of damage. A new, simple, and fast procedure for logging geomechanical drill cores is proposed, which allows UDi to be applicable at every stage of rock engineering projects. We used the UDi for the prediction of the spatial geometry of over-excavation along a tunnel. There is a good agreement between the variational trend computed using UDi and over-excavation along a tunnel observed at El Teniente mine, Chile. Moreover, the good correlation between rock mass quality rating from UDi and Rock Mass index (RMi) demonstrate the reliability of the UDi rating system. • Universal Discontinuity index (UDi) to characterize discontinuous rock masses. • The spatial prediction of the rock strength heterogeneity and anisotropy using UDi. • Pre-existing damage, Kinematic block instability, and potential of shear failure. • UDi to predict the geometry of over-excavation around tunnel and its uncertainty. • R-Dis-Frag computer package for real time-scale analysis of rock engineering design. [ABSTRACT FROM AUTHOR]

Using longitudinal data and a Difference-in-Difference approach, this paper examines how the mass inflow of Venezuelan (who speak Spanish as the natives) and non-Spanish-speaking (mainly Haitians) migrants to Chile has influenced the learning outcomes of native students, specifically the 6th graders in 2018. The evidence shows a decrease on standardized test scores, especially for male students (−0.072SD in Reading, −0.06SD in Math). Said effects are considerably greater in Reading when examining the migration of non-Spanish speakers (−0.099SD). When the shock is motivated by Venezuelan students, a decrease in Mathematics/Reading are observed in both male (−0.56SD/−0.067SD) and female students (−0.04SD/−0.035SD). Two hypotheses that may account for these effects are evaluated. First, a lack of human and financial resources to address these new educational demands. Second, native flight from public to private schools, especially involving higher SES or higher performance students. Results indicate that only the first hypothesis may account for the possible underlying mechanisms. [ABSTRACT FROM AUTHOR]

Chile is one of the ten most underfunded countries for conservation of protected areas in the world. The COVID-19 pandemic aggravated protected areas' funding situation by severely reducing tourism revenues. This paper studies whether Chilean households would be willing to support protected areas through donations or tariffs. Using a contingent valuation approach, we find that the average willingness to pay ranges from US$ 3 to US$ 8 per household per month, depending on specification. Estimated willingness to pay is 23% to 36% lower when households are asked to pay via tariffs instead of donations. We discuss our results relative to previous literature and evaluate its policy implications in the Chilean context. We find that a flat tariff sufficient for covering 70% of the current funding gap would be acceptable to 74% of Chile's households. • Chilean households would be willing to support protected areas through donations or tariffs. • About half of Chileans would be willing to pay either US$ 6 or US$ 8 per month, depending on the type of payment vehicle. • 74% of Chile's households would be willing to pay US$ 0.7 per month, which would cover about 70% of the current funding gap. [ABSTRACT FROM AUTHOR]

This paper presents an agent-based model of the technological adoption of solar panels, including potential adopters' characteristics and their interactions. This study analyzes the theoretical impact of seven social influence strategies on the adoption of solar panels by householders within a solar neighborhood in the Providencia district, Chile. In this case study, established adopters account for 0.9% of the population, opinion leaders for 1.3%, and individuals in the network for 97.8%. Considering the population's high-level ambition and tolerance of uncertainty, we found that householders are mainly characterized as optimizers (89.7%), followed by inquirers (7.6%), repeaters (2.3%), and imitators (0.3%) agents. Our agent-based simulation model evaluated the social influence strategies based on economic, environmental, and social benefits. The results show that social influence strategies lead to a 19.27% increase, on average, in the total number of adopters concerning the base case. Then, we performed a multi-objective analysis to select the best adoption strategy. These results show that selecting the most connected agents in the network is a robust strategy the decision-makers have environmental or financial concerns. However, if the decision-makers' primary interest is maximizing the diffusion scope of solar panel neighborhoods, random agent selection is the most advisable strategy, given its ease of implementation. [Display omitted] • Consumat approach and Campbell's paradigm were integrated into a simulation model. • The results from seven social influence strategies are compared. • Selective seeding and random seeding are found to be the most effective strategies. [ABSTRACT FROM AUTHOR]

Teacher quality is one of the most relevant factors influencing student learning. However, attracting and retaining skilled people to the teaching profession is challenging. In this paper, we study how making college tuition-free affects the pool of students pursuing a teaching career. We exploit the conjunction of two tuition-financing policies implemented in Chile: a scholarship introduced in 2011 for teaching majors, and a massive 2016 reform that made college tuition-free for students from households in the bottom 50% of the income distribution. We use the programs' differences in timing and eligibility criteria to study the effects free college had on the self-selection of students into teaching programs. We find that free college decreased the relative returns to pursuing a teaching career, making it substantially less popular among relatively poor high-performing students who now self-select into programs with higher returns. We find that the reform reduced the academic qualifications of the pool of students entering the teaching programs, which can negatively affect long-term teacher quality. [ABSTRACT FROM AUTHOR]

• Analytical study on a type of column base connection: Exposed Base Plate with Extended Anchor Bolts. • Excellent behavior in recent major earthquakes (e.g., 2010 Chile earthquake) • Plastic deformations occur only at the anchor bolts, and all other components of the connection (including the column) remain elastic. • Flag-shape, self-centering hysteretic behavior. • A rational design methodology is proposed and validated. This paper investigates the behavior of a ductile detail of exposed base plates. This detail consists of a base plate anchored to the concrete foundation through bolts extended to a steel chair configuration. The intention is to concentrate plastic strains mainly in the extended region of the anchor bolts, forcing the other connection components to remain elastic. The scientific background of this research consists of a series of sophisticated nonlinear finite element models subjected to a cyclic load protocol in the presence of an axial compressive force. The models were validated against an experimental test reported in the literature. Forces within the connection components, stresses, strain distributions, and deformation modes were examined. A total of sixteen three-dimensional nonlinear models were created using the ABAQUS simulation platform. The models were separated into two groups: the first consists of models with dimensions similar to the specimens tested in recent experimental programs reported in the past, while the second group simulates connections representative of mid-rise industrial frames. Building on the insights gained from the simulations of the first group, a methodology is proposed to design these column base connections. This suggested methodology is validated with the second group of simulations. Results indicate that the studied configuration detail presents some advantages compared with the traditional detail presented in Design Guide 1. For instance, plastic strains are developed almost exclusively in the anchor rods, and no damage is expected at the remaining components. Another essential characteristic is the exposed stretch length, with which it is possible to achieve a target design rotation without significant strain concentrations in the anchor rods. This characteristic facilitates post-earthquake inspections and repairs, and damage is virtually eliminated in the first story. [ABSTRACT FROM AUTHOR]

Chile is currently engaged in an energy transition process to meet ambitious greenhouse gas reductions and improved air quality indices. In this paper, we apply a long-term energy planning model, with the objective of finding the set of technologies that meet strong reductions of CO 2 emissions and of local P M 2. 5 concentrations. For this purpose, we use the existing ETEM-Chile (Energy-Technology-Environment-Model) model which considers a simplified version of the Chilean electricity sector that we extend to the residential and commercial sectors and to local concentration considerations. We propose an original approach to integrate in the same framework local and global emission constraints. Results show that to meet the goal of zero emissions by 2050, electrification of end-use demands increases up to 49.2% with a strong growth of the CO 2 marginal cost. It should be noted that this electrification rate is much lower than government projections and those usually found in the literature, in certain geographic areas in southern Chile with a wide availability of firewood for residential heating. Regarding local P M 2. 5 concentrations, our analysis shows that even without a specific emission reduction target, acceptable P M 2. 5 concentrations are achieved by 2045, due to first the emergence of more efficient, cleaner and cost-effective end-use technologies, in particular, residential firewood heaters, and second the use of drier and therefore less contaminating firewood. Achieving acceptable air quality as early as 2030 is also possible but comes with a high marginal cost of P M 2. 5 concentration. Our results illustrate the need for implementing effective public policies to (i) regulate the firewood heating market to increase its production and improve its environmental quality and (ii) incentivize the installation of efficient firewood heaters in the residential sector. [ABSTRACT FROM AUTHOR]

In the field of water management, desalination industry has faced various economic and environmental challenges. Renewable energies and the incorporation of operational strategies such as demand-side management have been able to contribute with the aim of facing them. Nonetheless, it is necessary to continue studying demand-side management for water supply systems emphasising it as a strategic tool to make operational decisions. This article presents a methodology based on a novel Mixed-Integer Linear Programming model in order to program the operation of a seawater reverse osmosis desalination plant with one pumping station for a desertic remote agricultural zone, in accordance with the principles of demand-side management. A photovoltaic solar plant connected to the grid is considered as a renewable energy source. The mathematical model aims to establish the optimal hourly operating load of the system that minimises the daily margin of purchased electricity costs minus sales income of generated electricity. The case study where the methodology is tested is an agricultural area in Northern Chile. The proposed methodology in this paper establishes the basis for future research and industrial applications, considering that it can be generalised to other geographical situations, as well as being modifiable to be adapted for more complex water supply systems and/or other renewable energy sources. • A novel optimisation model was developed to manage a water supply system operation. • The developed optimisation model is based on demand-side management principles. • Demand-side management enables more efficient use of renewable energy. [ABSTRACT FROM AUTHOR]

The problem of water scarcity in the world has gained great relevance in recent decades. One of the fields of study that has been developed as an ecological alternative to combat the water demand is the reuse of greywater. Greywater corresponds to domestic wastewater that excludes water from the toilet. These waters have the potential to be reused after simple treatments for non-potable uses. In the last decade, Chile has gone through the most intense mega-drought in its history. One of the most affected regions is the Coquimbo Region, located in the north-central zone, with a semi-arid climate and extensive agricultural activity. This paper presents the first results of pilot greywater treatment systems installed in rural public schools in the Coquimbo Region. In the first instance, different sorbent materials such as sand, zeolite, acid-activated carbon (AAC), base-activated carbon (BAC) and heat-activated carbon (HAC) were studied for the removal of organic matter and turbidity. It was found that the adsorbent materials based on carbon were more efficient for the removal of organic matter, registering maximum mean sorption capacities of 107.7 mg/g, 77.5 mg/g and 78.5 mg/g, for AAC, BAC and HAC, respectively. On the one hand, the treatment columns composed HAC, zeolite and sand, were very effective for removing turbidity, reaching removal percentages over 90%. On the other hand, pilot treatment systems were efficient in reaching the water quality levels required by Chilean legislation for the use of irrigation of recreational areas and services, and in some cases for the use of ornamental irrigation. The advantage of these systems is their simplicity and low installation cost. These systems have allowed savings of between 840 and 26,000 L per month, depending on the size of the school, which has allowed the watering of gardens. [Display omitted] • Heat-activated carbon and acid-activated carbon were effective for the adsorption of organic matter. • Sequential treatments columns containing heat-activated carbon, sand and zeolite had a great capacity for removing turbidity. • The pilot treatment systems installed in rural schools exhibited good results in greywater treatment. • Low-cost pilot treatment systems allowed the irrigation of gardens and green areas in rural schools. [ABSTRACT FROM AUTHOR]

• A new self-centering shear key geometry is proposed that eliminates residual displacements of the superstructure, using only the structure's own weight, geometry and conventional bearing pads to generate the required restoring force. • The proposed solution is simply a change in the kinematics of the bridge allowing superstructure's self-centering. • The new self-centering technique is used to analyze a typical Chilean bridge using a set of records classified by soil types, considering the three translational components of the ground motion components. The results indicate that the technique is feasible, but care needs to be taken in accounting for an increase in forces in the substructure. • The proposed shear key concept does not need additional devices such seismic isolators or energy dissipation elements. With a simple change of the geometry, the elimination of the residual displacements ensures the superstructure's self-centering behavior. Shear keys are elements in bridges designed to prevent or limit transverse unseating, rotation, and/or collapse of the superstructure responding to strong-intensity earthquake input ground motion, as well as to absorb breaking and various self equilibrating forces. During the 2010 Maule earthquake, Chile's highway infrastructure was seriously impacted. Shear key failures were endemic and did not function as intended. As a result, some bridges experienced partial or complete collapse. Even when the shear keys appeared to have worked, the superstructure exhibited large offsets, which required expensive repairs. An expensive retrofit of undamaged bridges was also carried out as a result of the inadequate response of the bridge infrastructure. This paper addresses the behavioral issues of bridges designed incorporating conventional shear keys and proposes an innovative self-centering concept that eliminates residual displacements in the superstructure. The self-centering shear key concept, as it will be termed here, makes use of the bridge self-weight as a restoring force to ensure self-centering. This concept proposal takes advantage of the kinematics of the bridge. The self-centering shear key concept was validated for a typical Chilean bridge via an extensive study that made use of nonlinear time history analyses. The results indicate that the increase in seismic demand on the substructure is small enough to maintain the bridge base structure in the elastic range while eliminating any residual displacements in the superstructure. [ABSTRACT FROM AUTHOR]

• Multidisciplinary investigation on seismic design guidelines for mid-rise wood frame buildings. • New seismic performance factors are proposed for wood-frame structures. • The proposed design guidelines allow optimized structural designs. • Less conservative seismic performance factors improve the cost-effectiveness ratio of wood frame structures. Seismic performance factors are an engineering tool to estimate force and displacement demands on structures designed through linear methods of analysis. In Chile, the NCh433 standard provides the regulations, requirements, and factors for seismic design of several structural typologies and systems. However, when it comes to wood frame structures, previous research has found that the NCh433 provisions are highly restrictive and result in over-conservative designs. Therefore, this paper presents an experimental and numerical investigation aimed at proposing new, less restrictive seismic performance factors for wood frame buildings. Following the FEMA P-695 guidelines and a novel ground motion set for subduction zones, this research embraced: (1) testing of several full-scale specimens, (2) developing of detailed and simplified numerical models, and (3) analyzing the seismic performance of a comprehensive set of structural archetypes. 201 buildings were analyzed and results showed that changing the current NCh433 performance factors from R = 5.5 & Δ max = 0.002 to R = 6.5 & Δ max = 0.004 decreases the average collapse ratio of wood frame structures by 13.3% but keeps the collapse probability below 20% for all the archetypes under study. Besides, it improves the cost-effectiveness of the buildings and enhances their competitiveness when compared to other materials, since savings of 40.4% in nailing, 15.9% in OSB panels, and 7.3% in timber studs were found for a 5-story building case study. Further analyses showed that the buildings designed with the new factors reached the "enhanced performance objective" as defined by the ASCE 41–17 standard, guaranteeing neglectable structural and non-structural damage under highly recurring seismic events. Finally, dynamic analyses revealed that the minimum base shear requirement C min of the NCh433 standard is somewhat restrictive for soil classes A, B, and C, leading to conservative results compared to archetypes where the C min requirement did not control the structural design. [ABSTRACT FROM AUTHOR]

Qualified teachers are a fundamental input for any education system. This paper presents the results of a large-scale intervention to attract high performing high-school students into the teaching profession in Chile. The intervention was a three-arm email campaign which made salient three types of motivations: intrinsic/altruistic, extrinsic, and prestige-related. The "intrinsic" and "prestige" arms reduced applications to teaching majors among high performers, while the "extrinsic" arm increased applications among low performers. A plausible interpretation could be that the "intrinsic" and "prestige" messages made more salient an issue that could otherwise be overlooked by high performing students (typically from more advantaged households), negatively impacting their program choice: that the social value of the teaching still lags behind other professions that are valued more by their families and social circles. In turn, the "extrinsic" arm made salient the recent improvements in the economic conditions of the teaching profession in Chile, thus appealing to low performing students who in general come from disadvantaged families and for whom monetary incentives are potentially more relevant. These results show that making salient certain types of motivations to the wrong target group could lead to undesired results. [ABSTRACT FROM AUTHOR]

This paper studies the causal effect of grade retention in primary school on juvenile crime in Chile. Implementing a fuzzy regression discontinuity design, we find that repeating an early grade in primary school decreases the probability of committing a crime as a juvenile by 14.5 percentage points. By estimating and simulating a dynamic model, we show that the RD result is mainly driven by two mechanisms related to the timing of grade retention. First, grade retention in early grades decreases the probability of grade retention in late primary school grades. Second, late grade retention in primary education has a positive and more relevant effect on crime than the direct effect in early grades. Our findings support the argument that, conditional on the decision to keep grade retention as an ongoing policy, the optimal implementation at the margin is to retain students in early grades in order to avoid retention in later ones. [ABSTRACT FROM AUTHOR]

The question about how to choose the best recycling policy is particularly relevant in developing countries. On the one hand, many of these countries have no national waste management strategies, with recycling programs emerging as an independent initiative financed by municipalities, mostly in urban areas. On the other hand, the municipal budget tends to be linked to the wealth of their inhabitants. Consequently, an efficient municipal resources allocation policy to support recycling programs is especially crucial for the most vulnerable population, often located in rural areas. In this paper, we address the problem of optimal allocation of resources for the adoption of a recycling program by municipalities located in both urban and rural areas of a developing country, determining the best combination between two options: increasing and redistributing existing resources. Our research methods involve comprehensive data collection and mathematical modelling, adopting a logistic regression model proposed in the literature, formulating a non-linear optimisation model, and implementing a resolution method. In addition, recycling policies with equivalent results are described and analysed, discussing their political feasibility and economic efficiency. To illustrate our proposal, the case of Chilean municipalities is considered. Chile is a country from the Global South that belongs to the OECD and can be therefore compared to other documented cases. Although no official national data is available, we were able to collect figures by requesting information from every municipality in the country. The obtained results show an important lack of resources at the national level in MSWM, especially affecting rural areas. In this context, equivalent recycling policies with combined options could better favour rural municipalities. However, the average probability for the adoption of a recycling program by municipalities, although shows slight increases, is not enough for a substantial change towards a more sustainable waste management model. Our results illustrate the gap between urban and rural municipalities, the need to inject important funds into the system as a whole, and open the question of whether a more direct 'command and control' policy is required instead of just trusting the individual initiative of each municipality, even if more resources are provided. [ABSTRACT FROM AUTHOR]