Добірка наукової літератури з теми "Long-term scenarios analysis"

In the paper alternatives for expansion of the Macedonian electricity supply system are presented. MESSAGE tool is used for modelling the system, for developing the scenarios, to analyse cost optimal energy pathways and to determine the optimal electricity generation technology mix. The calculations for the period 2020-2050 are made in a 5-year interval. Two scenarios are developed: Scenario 1 – BAU (Business as Usual) scenario, where the current energy structure prevailed, with trends like the current development. The electricity demand is satisfied by coal-fired thermal power plants, gas-fired thermal power plants, hydro power plants and renewable power plants. Scenario 2 – Green scenario, where gas-fired thermal power plants and nuclear power representative with small modular reactors are base load technologies, and also intensive construction of production capacities on renewable energy sources is forced. By making further analysis, the possibility of flexibility in the construction of new facilities within the interval, economic indicators, and appropriate impact on the environment are obtained. In order to make an economic analysis for a particular technology, calculations are made for parameters that are standard for projects, such as: net present value, benefit – cost ratio, payback period and internal rate of return. The environmental impact is analysed of aspect of CO2 emissions.

Electricity plays a vital role in the economic development and welfare of countries. Examining the electricity situation and defining scenarios for developing power plant infrastructure will help countries avoid misguided policies that incur high costs and reduce people’s welfare. In the present research, three scenarios from 2021–2040 have been defined for Iran’s electricity status. The first scenario continues the current trend and forecasts population, electricity consumption, and carbon dioxide emissions from power plants with ARIMA and single and triple exponential smoothing time series algorithms. As part of the second scenario, only non-hydro renewable resources will be used to increase the electricity supply. By ensuring the existence of potential, annual growth patterns have been defined, taking into account the renewable electricity generation achieved by successful nations. The third scenario involves integrating operating gas turbines into combined cycles in exchange for buyback contracts. Economically, this scenario calculates return on investment through an arrangement of various contracts for the seller company and fuel savings for the buyer.

Drought is a meteorological disaster that has serious economic and environmental impacts. Therefore, for drought assessment, it is important to not only analyze the current state of drought using observed data but also future droughts by considering climate change. Although shared socioeconomic pathways (SSPs) have been developed, studies regarding their application in drought analysis in Korea are insufficient. In this study, the standardized precipitation index (SPI) and reconnaissance drought index (RDI) for future droughts in Korea were calculated and analyzed using climate data based on SSP scenarios. The precipitation and temperature data from SSP1-2.6 and SSP5-8.5 scenarios were analyzed. In both scenarios, temperature and precipitation increased toward the long-term future, with the increase being more in the SSP5-8.5 scenario than in the SSP1-2.6 scenario. Using these data, the number of drought occurrences was found to be smaller, and the two drought indices were found to be lower in SSP5-8.5 scenario than in the SSP1-2.6 scenario, implying that more severe droughts may occur in the former than in the latter. In addition, in SSP1-2.6 scenarios, both SPI and RDI increased toward the long-term future, while in SSP5-8.5 scenario, SPI increased, and RDI decreased toward the long-term future.

Multi-criteria decision analysis (MCDA) of regional level long-term forest management scenarios was conducted by applying spatially explicit information to examine the trade-offs between ecological, economic and social impacts. Interval scale judgements were applied to mapped and numerical information jointly, while assessing the performance of alternative scenarios. The experts relied mostly on the numerical information, with which they might have been more confident and familiar. The weight elicitation was based on SMART using Swings (SMARTS) and SMART Exploiting Ranks (SMARTER). SMARTS resulted in two scenarios being quite equal either due to experts truly considering them equally important or being unconfident to express their weights applying SMARTS. SMARTER was considered more understandable, but lead to total utilities having wider range. However, impact information had a greater effect on the overall utility than the weighting. Future insights include use of dynamic approach, considering the issue more from ecosystem services point of view and tighter integration of participatory MCDA and geographic information systems (GIS).

Despite the great advantages of high-temperature polymer electrolyte membrane (HT-PEM) fuel cells over the low-temperature (LT) PEM alternative, such as enhanced reaction kinetics and higher tolerance against impurities like CO due to the higher operation temperature, the achievement of high lifetimes still remains a challenge. In order to improve the durability of the fuel cell, extensive research has been carried out on alternatives for the individual components. For this reason, this paper conducted extended long-term tests with three three membrane electrode assemblies (MEAs) from one manufacturer under different operational scenarios. The MEAs differed mainly by the membranes used and showed significantly different behaviors. While the first MEA reached the end of life already after 2600 h, the second one could pass 9800 h almost without any problems. The third MEA proved resistant to adverse conditions. For all three MEAs, extensive electrochemical characterizations and μ-CT examinations for the analysis of long-term stability are shown.

Generation of realistic scenarios is an important prerequisite for analyzing the reliability of renewable-rich power systems. This paper satisfies this need by presenting an end-to-end model-free approach for creating representative power system scenarios on a seasonal basis. A conditional recurrent generative adversarial network serves as the main engine for scenario generation. Compared to prior scenario generation models that treated the variables independently or focused on short-term forecasting, the proposed implicit generative model effectively captures the cross-correlations that exist between the variables considering long-term planning. The validity of the scenarios generated using the proposed approach is demonstrated through extensive statistical evaluation and investigation of end-application results. It is shown that analysis of abnormal scenarios, which is more critical for power system resource planning, benefits the most from cross-correlated scenario generation.

The EU aims at increasing the use of renewable energy sources (RES), mainly solar-photovoltaic (PV) and wind technologies. Projecting the future, in this respect, requires a long-term energy modeling which includes a rate of diffusion of novel technologies into the market and the prediction of their costs. The aim of this article has been to project the pace at which RES technologies diffused in the past or may diffuse in the future across the power sector. This analysis of the dynamics of technologies historically as well as in modeling, roadmaps and scenarios consists in a consistent analysis of the main parameters of the dynamics (pace of diffusion and extent of diffusion in particular markets). Some scenarios (REMIND, WITCH, WEO, PRIMES) of the development of the selected power generation technologies in the EU till 2050 are compared. Depending on the data available, the learning curves describing the expected development of PV and wind technologies till 2100 have been modeled. The learning curves have been presented as a unit cost of the power versus cumulative installed capacity (market size). As the production capacity increases, the cost per unit is reduced thanks to learning how to streamline the manufacturing process. Complimentary to these learning curves, logistic S-shape functions have been used to describe technology diffusion. PV and wind generation technologies for the EU have been estimated in time domain till 2100. The doubts whether learning curves are a proper method of representing technological change due to various uncertainties have been discussed. A critical analysis of effects of the commonly applied models for a long-term energy projection (REMIND, WITCH) use has been conducted. It has been observed that for the EU the analyzed models, despite differences in the target saturation levels, predict stagnation in the development of PV and wind technologies from around 2040. Key results of the analysis are new insights into the plausibility of future deployment scenarios in different sectors, informed by the analysis of historical dynamics of technology diffusion, using to the extent possible consistent metrics.

The work describes new method of graphical analysis developed for freshwater ecosystems and three scenarios of their transformation were documented. The parameters of the structure-forming groups of hydrobionts, which determine their stability, are established. The transformations recorded in natural or natural-technogenic systems were analyzed using a similar method. The similarity of those scenarios allows us to refer all the considered systems to the systems of the fourth level of complexity.

This study explored energy solutions for Ghana by analysing alternative pathways from 2010 to 2040. The Long-range Energy Alternating Pathways (LEAP) tool was used the scenarios analysis. Four scenarios were developed based on key influencing factors identified in the literature. These are Base case, Coal, Modest Renewable Energy Technology (RET), and High RET scenarios. The Base case scenario was based on government-planned expansion and assumed no shift in policy. The Coal scenario assumed the same expansion trend as Base case with introduction of coal plants replacing a percentage of natural gas generation. Modest and High RET scenarios examined the development of the system with increased renewable energy integration. The results revealed that overall benefits are achieved with higher integration of renewable energy technologies. Economic benefits of 0.5 –13.23% is achieved in the RET scenarios depending on the cost development over the 30 year study period. The high RET offers the highest economic and environmental benefits. Subsequently, the optimal development of the system was examined using the LEAP/OSeMOSYS (Open Source Energy Modelling System) optimisation methodology. The least cost system developed by LEAP (Optimum scenario), was used as a reference to examine future possible energy policy direction in Ghana. The policy constraints analysed included emission targets, carbon taxes and transmission, distribution losses improvements and demand side efficiency. The results show that: suitable policies for clean power generation have an important role in CO2 mitigation in Ghana. The introduction of carbon minimisation policies will also promote diversification of the generation mix with higher penetration of renewable energy technologies. The study proposes promoting energy efficiency and improvement in transmission and distribution losses and utilisation of renewable energy as the best energy strategy for Ghana. Ghana needs ambitious targets, policies and implementation strategies to enhance energy efficiency, and decrease demand in the long term. Stable funding and promotion of transparent policies are required to promote high development of renewable energy technologies.

With the rapid development of the social economy, the industrialization and urbanization process is accelerating, and the harm of serious environmental pollution has become increasingly evident. Among them, the atmosphere as the essential factor for human survival, has been a threat to survive and healthy of humans and other organisms. And the pollution sources have the diversity and specificity. This paper analyzes the causes of the formation of Shanghai haze pollution, as well as the characteristics and sources of major PM2.5 components. According to the analysis, point out that the adverse weather conditions is the culprit for the formation of haze pollution, and air pollutants are the accomplices. Base on the specific nature of pollution sources and regional particularity, to develop a strategic plan for Shanghai haze governance. To optimize and maintain the urban environment, it requires the city government to develop scientific plans for the controlling of economy and key sources of pollution. Urban residents also need to consciously participate into the environmental protection work, advocating green and low-carbon life, and friendly living and travel habits. Overall, the Shanghai government should make a good job in green environmental protection from the details.

The Swedish National Debt Office (SNDO) is the Swedish Government’s financial administration. It has several tasks and the main one is to manage the central government’s debt in a way that minimizes the cost with due regard to risk. The debt management problem is to choose currency composition and maturity profile - a problem made difficult because of the many stochastic factors involved.

The SNDO has created a simulation model to quantitatively analyze different aspects of this problem by evaluating a set of static strategies in a great number of simulated futures. This approach has a number of drawbacks, which might be handled by using a financial optimization approach based on Stochastic Programming.

The objective of this master’s thesis is thus to apply financial optimization on the Swedish government’s strategic debt management problem, using the SNDO’s simulation model to generate scenarios, and to evaluate this approach against a set of static strategies in fictitious future macroeconomic developments.

In this report we describe how the SNDO’s simulation model is used along with a clustering algorithm to form future scenarios, which are then used by an optimization model to find an optimal decision regarding the debt management problem.

Results of the evaluations show that our optimization approach is expected to have a lower average annual real cost, but with somewhat higher risk, than a set of static comparison strategies in a simulated future. These evaluation results are based on a risk preference set by ourselves, since the government has not expressed its risk preference quantitatively. We also conclude that financial optimization is applicable on the government debt management problem, although some work remains before the method can be incorporated into the strategic work of the SNDO.

Ethiopia is one of the sub-Saharan Africa countries whose energy depends on traditional use of biomass such as wood, charcoal, agricultural residues and animal dung. The traditional use of biomass mainly wood and charcoal leads the country to massive deforestation and forest degradation. Negative environmental impacts from poorly managed municipal solid waste are also serious problems in the country. Moreover, there is a wide range of fossil fuels demand in the country fully covered by importing which results to a significant expenditure from the country’s budget. This study investigates the long-term shifts in bioenergy use of the country and evaluates the expected social, environmental and economical implications. For this purpose, three scenarios are formulated within a timeframe that goes from 2013 to 2030. The baseline scenario assumes the existing energy practices of the country would undergo no significant change in the future while the moderate shift and high shift scenarios consider the long-term shifts in bioenergy use with and without considering constraints respectively. In this context, long-term shifts means: transition from traditional use of biomass to efficient and modern in the household sector, biofuels deployment in the transport sector, introduction of agricultural residues as a fuel for cement production, and electricity generation from bagasse and municipal solid waste. To model and analyze the scenarios, the long-range energy alternatives planning system (LEAP) software tool is used. Taking the results of high shift scenario by 2030, the use of improved wood stoves and fuel switch stoves could save 65 million tons of wood. The foreign currency saving from using biofuels and agricultural residues as fossil fuels substitute would reach to 674 million USD. The greenhouse gas emissions reduction is equivalent to 46 million tons of CO2e which is about 18.4% of the CO2e abatement target of the country for 2030. The corresponding revenue from carbon trading schemes would reach to 231 million USD. Electricity generation from bagasse and municipal solid waste would be 3,672 GWh that is around 3.7% of the total electricity generation target for 2030.

Die Nutzung historisch solider Lastannahmen, wie sie zum Beispiel die VDV Richtlinie 152 in der Fassung von 1992 festlegt, ist für die Festigkeitsauslegung neuartiger Straßen- und Stadtbahnfahrzeuge unzureichend, da die Annahmen und Methoden der Komplexität und insbesondere der Nichtlinearität moderner Fahrzeugkonzepte keine Rechnung tragen. Diese Arbeit zeigt auf, wie sich entstandene Lücken in den Lastannahmen durch Simulation und Messung von Fahrzeug und Gleis analysieren, verstehen und schließen lassen. Den Kern bildet dabei der Einsatz detaillierterer Simulationsmodelle von Fahrzeug und Gleis, deren Eingangsdaten mit Hilfe von Messungen gewonnen und deren Ausgangsdaten mit ihnen verifiziert und ergänzt werden müssen. Hierfür werden Methoden und Werkzeuge entwickelt, die ein ein vielseitiges Baukastensystem für die Fahrzeuganalyse, Modellvalidierung und Datenbewertung bilden, und zu sicheren Lastannahmen für die Fahrzeugauslegung führen.

University of Technology, Sydney. Faculty of Engineering and Information Technology.
NO FULL TEXT AVAILABLE. Access is restricted indefinitely. The hardcopy may be available for consultation at the UTS Library.
NO FULL TEXT AVAILABLE. Access is restricted indefinitely.

碩士
國立交通大學
工學院碩士在職專班永續環境科技組
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Developing various green energies is important in Taiwan because Taiwan has very limited domestic energy resources and the reduction of greenhouse gases has become an essential national pressure. The biomass energy is thus currently promoted. However, most local biomass energy studies were primarily based on foreign experiences and overlooked Taiwan’s specific natural environment and climate characteristics. As a result, the benefit for developing biomass energy crops in Taiwan was not properly assessed. Furthermore, energy crop development should not affect regular food supply. Therefore, this study was initiated to establish a method to evaluate the benefits of growing energy crops on long-term uncultivated lands in Taiwan. The proposed method includes five major steps: district division, energy crop selection, benefit analysis, optimization model establishment, and scenario analysis. The entire nation is divided into three major biomass energy districts based on the K�夗pen climate classification and administrative boundaries. For selecting suitable energy crops to grow in each district, various geological and meteorological factors are evaluated, including soil, rainfall, temperature and sunlight resources. Expected harvest quantities and biomass energy yield rates are also evaluated for assessing the suitabilities for raising various crops. The benefit analysis is implemented for estimating environmental, energy yield and economic benefits. A two-step near-optimum model is applied. The first step relaxes the minimal demand of biodiesel and gasohol by 5% of the total demand. Then, the growing area determined in the first step is set as the upper limit in the second step to find the solution with the best benefit. Eight possible scenarios for various bioethanol and biodiesel demands were analyzed. In each scenario, the optimal growing area of each energy crop and associated benefits were determined. According to the results, scenario 6, 100% usage of B2 biodiesel and E3 gasohol, shows the best unit benefit, about 2.35 million ton eCO2 decrease per hectare.

Die Nutzung historisch solider Lastannahmen, wie sie zum Beispiel die VDV Richtlinie 152 in der Fassung von 1992 festlegt, ist für die Festigkeitsauslegung neuartiger Straßen- und Stadtbahnfahrzeuge unzureichend, da die Annahmen und Methoden der Komplexität und insbesondere der Nichtlinearität moderner Fahrzeugkonzepte keine Rechnung tragen. Diese Arbeit zeigt auf, wie sich entstandene Lücken in den Lastannahmen durch Simulation und Messung von Fahrzeug und Gleis analysieren, verstehen und schließen lassen. Den Kern bildet dabei der Einsatz detaillierterer Simulationsmodelle von Fahrzeug und Gleis, deren Eingangsdaten mit Hilfe von Messungen gewonnen und deren Ausgangsdaten mit ihnen verifiziert und ergänzt werden müssen. Hierfür werden Methoden und Werkzeuge entwickelt, die ein ein vielseitiges Baukastensystem für die Fahrzeuganalyse, Modellvalidierung und Datenbewertung bilden, und zu sicheren Lastannahmen für die Fahrzeugauslegung führen.

This chapter considers the question of whether an arbitrator may also adopt a mediation function or whether the dual roles are antithetical. It tests that hypothesis by engaging in a cost-benefit analysis of differing scenarios when mediation is utilized in an arbitral context. The prime comparison is between parallel mediation with a separate neutral and the alternative of a dual-role neutral. The three key points are: there should be much more mediation occurring at the international level, regarding both potential and actual arbitral disputes; a commercially minded arbitrator concerned for the parties’ good faith should encourage mediation where appropriate, in particular, when an adjudicated outcome will not be in the interests of either, usually because the dispute is a small part of a long-term relationship that can risk that relationship no matter who wins; and, while informed party autonomy should always support a dual-role neutral, in most factual permutations, informed parties could be expected to prefer parallel mediation provided there is full cooperation between mediator and arbitrator. The chapter argues that the relative benefits of the use of dual-role neutrals would be greatly outweighed by the costs in fairness and efficiency, and the inevitable need for a sub-optimal design of either or both dispute processes. The benefits would also be separately outweighed by the risks of significant disruption to any ensuing arbitration if a dual-role neutral fails to achieve a settlement.

New drivers of Russian nationalism appeared in the 1990s, making possible either a return to imperial nationalism, as a reaction to globalisation, or, in response to ethnic conflict, a rise in ethnic nationalism. This chapter analyses the changing balance of elite and mass preferences and their influence on the choices made by the Russian government. Recently, in a sharp reversal of long-term post-Soviet trends, elite attitudes have shifted in favour of imperial projects beyond Russia’s borders. Another long-term trend has also accelerated: that of valuing military might over economic power in international relations. Anti-Muslim sentiment simmering across the Russian Federation might inspire ethnic nationalism. However, this chapter shows that mass-level attitudes towards Muslims correlate negatively with attitudes towards the USA. Given the current high levels of anti-US sentiment, the ethnic scenario seems unlikely – for the moment.

Abstract With the onslaught of the pandemic, countries worldwide were grappling with a humanitarian and economic crisis and India was no exception. In an effort to minimize its adverse impact, fiscal and monetary authorities stepped forward with conventional and unconventional measures to address supply and demand-side issues. Keeping in mind the macroeconomic scenario existing in India in June 2020, the authors decided to examine the important measures/policies announced by the Government and Reserve Bank of India and evaluate its impact on the country. Part 1 of the book looks at the preceding economic growth trends from 2010 onwards, examines the impact of the virus on India’s economic growth, provides inputs for Budget 2021–22 and analyses the impact on the country’s GDP, taking into consideration Q1FY22 numbers. Part 2 critically analyses policy initiatives, short-term and long-term structural reforms undertaken by the Government and RBI. Part 3 sketches out a roadmap of policy inputs and suggestions which need Government focus to build the country into an Atmanirbhar Bharat and make India, a self-reliant nation.

Volcanoes represent complex geological systems capable of generating many dangerous phenomena. To evaluate and manage volcanic risk, we need first to assess volcanic hazard (i.e., identify past volcanic system behavior to infer future behavior. This requires acquisition of all relevant geological and geophysical information, such as stratigraphic studies, geological mapping, sedimentological studies, petrologic studies, and structural studies. All this information is then used to elaborate eruption scenarios and hazard maps. Stratigraphic studies represent the main tool for the reconstruction of past activity of volcanoes over time periods exceeding their historical record. This review presents a systematic approach to volcanic hazard assessment, paying special attention to reconstruction of past eruptive history. It reviews concepts and methods most commonly used in long- and short-term hazard assessment and analyzes how they help address the various serious consequences derived from the occurrence (and nonoccurrence in some crisis alerts) of volcanic eruptions and related phenomena.

Volcanoes represent complex geological systems capable of generating many dangerous phenomena. To evaluate and manage volcanic risk, we need first to assess volcanic hazard (i.e., identify past volcanic system behavior to infer future behavior. This requires acquisition of all relevant geological and geophysical information, such as stratigraphic studies, geological mapping, sedimentological studies, petrologic studies, and structural studies. All this information is then used to elaborate eruption scenarios and hazard maps. Stratigraphic studies represent the main tool for the reconstruction of past activity of volcanoes over time periods exceeding their historical record. This review presents a systematic approach to volcanic hazard assessment, paying special attention to reconstruction of past eruptive history. It reviews concepts and methods most commonly used in long- and short-term hazard assessment and analyzes how they help address the various serious consequences derived from the occurrence (and nonoccurrence in some crisis alerts) of volcanic eruptions and related phenomena.

This book forms part of a larger research project at the University of the Free State (UFS) in South Africa that is investigating the consequences of mining for local communities and mining towns. The book analyses the current situation in Emalahleni and considers the likelihood of a just transition across a range of fields. The case study of the mining city of Emalahleni (‘place of coal’) in South Africa, formerly Witbank, both exemplifies and illuminates how the energy scenario plays out in one major mining city and in turn casts light on that scenario. The authors did not understand the inequalities and social stratification that appear to permeate the mining industry and mining towns. Furthermore, the authors did not understand how changes in the mining environment and government policy affect mineworkers and mining towns. In addition, there is the potential effect of mine closure. Sometimes closure is the result of resource depletion or changes in the market. In other cases, such as Emalahleni, it is the result of an economic transition. Whatever the reason, mining seldom results in long-term prosperity. The problem is that virtually nobody plans for closure or economic decline. In many cases, communities and local governments ignore closure. Therefore, this book investigates the current situation in Emalahleni and considers the implications of possible mine closure. Finally, the book assesses the notion of power in decision-making. The power of capital and its effects on local settlements and communities are crucial to understanding local responses to economic transitions.

AbstractAgainst the background of several European countries implementing capacity remuneration mechanisms (CRM) as an extension to the energy-only market (EOM), this chapter provides a quantitative assessment of the long-term cross-border effects of CRMs in the European electricity system. For this purpose, several scenario analyses are carried out using the electricity market model PowerACE. Three different market design settings are investigated, namely, a European EOM, national CRM policies, and a coordinated CRM. The introduction of CRMs proves to be an effective measure substantially shifting investment incentives toward the countries implementing the mechanisms. However, CRMs increase generation adequacy also in the respective neighboring countries, indicating that free riding occurs. A coordinated approach therefore seems preferable in terms of both lower wholesale electricity prices and generation adequacy.

AbstractWe present a new approach to advance methods of climate change impact and adaptation assessment within a risk framework. Specifically, our research seeks to test the feasibility of applying impact models across sectors within a standard analytical framework for representing three aspects of potential relevance for policy: (i) sensitivity—examining the sensitivity of the sectors to changing climate for readily observable indicators; (ii) urgency—estimating risks of approaching or exceeding critical thresholds of impact under alternative scenarios as a basis for determining urgency of response; and (iii) response—determining the effectiveness of potential adaptation and mitigation responses. By working with observable indicators, the approach is also amenable to long-term monitoring as well as evaluation of the success of adaptation, where this too can be simulated. The approach focuses on impacts in climate-sensitive sectors, such as water resources, forestry, agriculture or human health. It involves the construction of impact response surfaces (IRSs) based on impact model simulations, using sectoral impact models that are also capable of simulating some adaptation measures. We illustrate the types of analyses to be undertaken and their potential outputs using two examples: risks of crop yield shortfall in Finland and impact risks for water management in the Vale do Gaio reservoir, Portugal. Based on previous analyses such as these, we have identified three challenges requiring special attention in this new modelling exercise: (a) ensuring the salience and credibility of the impact modelling conducted and outputs obtained, through engagement with relevant stakeholders, (b) co-exploration of the capabilities of current impact models and the need for improved representation of adaptation and (c) co-identification of critical thresholds for key impact indicators and effective representation of uncertainties. The approach is currently being tested for five sectors in Finland.

The paper describes the main features of the system of dynamic models for the analysis and forecasting of macroeconomic interactions of the markets of goods, labor, investment and money, which make it possible to use this system in a step-by-step procedure for constructing an experimental assessment of the relative changes in macroeconomic indicators under the influence of sectoral structural shifts in various scenarios of long-term systemically balanced development of the economy.

Considering Latin American economies have introduced various forms of attaining combat the economic crisis mostly through short-term policies based on credit incentive and increased public expenditure in order to revive the same; however, a long-term strategy where inclusive and sustainable growth which can be clearly discerned through innovation can play a key role prioritizing necessary. Thus in the course of this chapter create an analysis of the benefits of innovation and technological development taking into account the current state in Latin America and the possible scenarios in which technology serves as an important tool for economic and social development which translates into basic cornerstone for business and growth enhancer.

The chapter presents the evolution of potential ESG risks in the healthcare sector related to striving to provide the best care for patients. Based on the literature and selected examples, the analysis of this problem will indicate potential risks of the main factors and tools that can help manage this risk in the healthcare sector. There is a research gap in the literature; there is a lack of detailed discussion and research allowing to establish the relationship between ESG factors and finances. Particular emphasis is placed on social pillar, which in the authors' opinion is critical to the functioning of the healthcare sector, especially from the face of COVID-19. The authors proposed a map to identify potential risk and possible scenarios of action in the long term. The main assumption of the study is that the implementation of ESG potential risk management leads in the long run to sustainable development in the healthcare sector.

Humanitarian Supply Chain is central to the capacity building in the eco-communities which are located in the disaster prone regions. In this study, an attempt has been made to develop a system dynamics model of humanitarian supply chain in order to capture causal dynamics and inter linkages within the system under investigation and suggest some critical intervention strategies for enhancing overall performance. An economic sub-sector base model for the Indian tribal communities has been calibrated and used for simulation analysis as a reference case-study. Conclusion & Results: It has been established through the simulation results that the success of short-term relief work lies in the long-term capacity building and, is critical to the performance of both current and future humanitarian operations and programs. The scenarios studied in this paper are with respect to those crucial decision environments and their underlying complexities which create an inherent endogenous dynamics perpetuated by various stakeholders giving functional response towards the humanitarian supply chain.

A variety of sustainability scenarios (e.g., IPCC’s Emissions Scenarios) have been described toward a sustainable society. While many of them aim at solving climate change problems and they often assume various low-carbon technologies, the problem is that such scenarios hardly examine their feasibility from the viewpoint of resource depletion. In particular, copper is a critical base metal because introducing low-carbon technologies (e.g., electric vehicles and wind power generators) may induce copper consumption. To assess feasibility of existing sustainability scenarios, this paper proposes a method for estimating long-term copper demand based on those scenarios. Our method proposes an integrated model that evaluates world copper demand from two principal aspects of influencing copper consumption — (1) the building of social infrastructure and (2) new products that might disseminate in the future (e.g., electric vehicles and photovoltaic systems). A case analysis on a long-term energy scenario is carried out. Its results reveal that the cumulative copper consumptions in the world exceed the copper reserved in the earth by 2040. The increase in copper consumptions results mainly from world economic growth led by developing countries, while the dissemination of electric vehicles and photovoltaic systems has a minor impact on the consumption increase.

Deep learning algorithms are becoming default solution for application in business processes where recognition, identification and automated learning are involved. For human identification, analysis of various features can be applied. Face feature analysis is most popular method for identification of person in various stages of life, including children and infants. The aim of this research was to propose deep learning solution for long-term identification of children in educational institutions. Previously proposed conceptual model for long-term re-identification was enhanced. The enhancements include processing of unexpected persons’ scenarios, knowledge base improvements based on results of supervised and unsupervised learning, implementation of video surveillance zones within educational institutions and object tracking results’ data chaining between multiple logical processes. Object tracking results are the solution we found for long-term identification realization.

The realistic study of dynamic accident context is an invaluable tool to address the uncertainties and their impact on safety assessment and management. The capacities of the Performance Evaluation of Teamwork procedure for dynamic context quantification and determination of alternatives, coordination and monitoring of human performance and decision-making are discussed in this paper. The procedure is based on a thorough description of symptoms during the accident scenario progressions (timelines) with the use of thermo-hydraulic model and severe accident codes (MELCOR and MAAP). The opportunities of PET procedure for context quantification are exemplified for the long-term station blackout (LT SBO) accident scenario at Fukushima Daiichi #1 and an hypothetic unmitigated LT SBO at Peach Bottom #1 Boiling Water Reactor Nuclear Power Plants. The context quantification of these LT SBO scenarios is based on the IAEA Fukushima Daiichi accident report, “State-of-the-Art Reactor Consequence Analysis” and thermo-hydraulic calculations made by using MAAP code at the EC Joint Research Centre, Institute for Energy and Transport, Nuclear Reactor Safety Assessment Unit.

Paper presents the overall scope and actual results of the project for evaluation of representative scenarios for reuse of conditionally released materials from decommissioning. Aim of the project is to evaluate the possibilities of reuse of conditionally released steels and concrete in technical constructions which guarantee the long-term preservation of design properties over periods of 50–100 years. Interaction of conditionally released materials with public is limited and predictable due to design and purpose of selected constructions and due to fact that in many scenarios these materials are embedded in non-radioactive materials such as bars in reinforced concrete. Worker’s scenarios for preparation, operation and maintenance of these constructions are analysed in detail including the manufacturing of elements for these constructions. Project aims to evaluate the scenarios of reuse of conditionally released materials in a complex way in order to develop the data for designers of scenarios and to evaluate the volumes of conditionally released materials based on facility (to be decommissioned) inventory data. The long-term constructions considered are bridges, tunnels, roads, railway constructions, industrial buildings, power industry equipment and others. Evaluation covers following areas: • Analysis of activities for manufacturing of reinforcement bars, rolled steel sheets and other steel elements and analysis of activities for construction of evaluated scenarios in order to evaluate the external exposure of professionals performing these activities; • Analysis of external exposure of professionals involved in operation and maintenance of the long-term constructions; analysis of external exposure of public groups which are exposed to evaluated constructions; • Analysis of internal exposure of public groups from the radionuclides released from the evaluated scenarios based on models for migration of radionuclides from the long-term constructions to critical groups of public; • Based on evaluation of external and internal exposure both for public and workers, maximal concentration of individual radionuclides is defined for construction elements of evaluated scenarios, manufactured from conditionally released materials; • Evaluation of volumes of steels and concrete in the frame of a decommissioning project which fulfil the defined radioactivity concentration limits. Visiplan 4.0 3D ALARA software is used for evaluation of external exposure of professionals and public, GOLDSIM software for evaluation of internal exposure of public and OMEGA code for evaluation of volumes of conditionally releasable materials. Several other parallel papers proposed for ICEM 11 are presenting selected details of the project.

Bio-based materials end of life is analysed from straw builders and farming practices. This paper proposes a classification of constructive straw systems according to their selective disassembly processes. According to EN 15804 standard, end-of-life (EoL) cycle analysis scenarios are used to create Environmental Product Declarations (EPD). These data will be used: - for architectural projects conception in respect to“RE2020” new French regulation. - as an awareness-raising approach for the long term design of constructive systems.

Analyzing railway critical scenarios usually involves a large team of diverse railway abilities and skills. This paper presents a formal modeling pattern for Hierarchical Colored Petri Nets (HCPN) in modeling railway safety critical scenarios. Indeed, under the French project called “PERFECT”, our long-term objective is to formalize and automate a significant part of railway scenarios modeling. The purpose of this contribution is to bring a first proposition of a standardized modeling way able to deal with the models complexity resulting from the various modeling capabilities for railway scenarios. In fact, HCPN modeling freedom is preventing from accurate information aggregation and a beneficial use of those models in an overall safety analysis. The proposed pattern is based on modular High Level Petri Nets and consists in describing all the railway scenario episodes while incorporating most relevant safety components of the system, such as safety regulation procedures, interlocking and even human involvement, enabling a larger gathering of information and allowing the study of diverse issues in a same global model. This work intends to bring a concrete and reusable HCPN pattern for modeling in order to facilitate studies of accidental scenarios considering automatic mechanisms and human tasks. A concrete application of the pattern was made for the real accidental scenario of “Saint Romain en Gier”.

This article proposes the management of information through the study and analysis of Colombian export scenarios that serve as a reference to articulate strategic nodes, for which an epistemological approach is proposed from a perspective of triangulation of techniques that allows a comprehensive approach in relation to the study of the external market of Colombia. This process is achieved through a comparative and complementary analysis of three techniques: Markov chains, forecasting techniques and mathematical functions. The behavior of sales is transformed into estimates of future behavior that establish a guiding mapping of the production levels that make the supply chain more dynamic. It is recommended to use time series techniques for short- and medium-term forecasts, while Markov chains for prediction and analysis of the sales structure in medium- to long-term forecasts, supported by median predictions through the use of mathematical functions.

There is a large number of studies about energy long term trends and policies, published by national and international government organisations. Commercial companies, particularly manufacturers of power generation equipment, can take benefit of these studies to test the robustness of long term technology development strategies. Scenario Planning and System Dynamics have been used by the government organisations to study energy policies. In this paper an application of this methodology is proposed for manufacturers of power generation equipment, in particular gas turbine manufacturers. A generic company is used as an illustrative example, against scenarios produced by the International Institute for Applied System Analysis. A System Dynamics model is proposed, simplifications and assumptions are discussed, the type of results that can be obtained is shown and some recommendations are suggested for the construction of more realistic models.

Within the ongoing global transition process towards renewable energies, gas turbines can play a significant role due to their ability to provide flexible and dispatchable power that compensates for the inherent volatility of renewable power generation. While being important for the stability of the electricity grid, this flexible mode of operation may result in a significant increase in thermo-mechanical stress for the gas turbine components. The demand for a constantly high level of performance and availability despite these challenges requires the employment of comprehensive monitoring tools. While different monitoring tools may vary in detail, a common core element is the inherent model capability to predict the ideal operational characteristics of the gas turbine for varying boundary conditions. In literature, various approaches are suggested to generate these gas turbine models. Within the present study, the authors apply a data-driven and a physically based modeling approach to two real long-term monitoring scenarios and compare different evaluation metrics. The overall goal of the study is the identification of advantages and disadvantages of the investigated modeling approaches depending on the monitoring scenario. The first part of the study takes the perspective of a gas turbine operator mainly focusing on the monitoring of the thermodynamic performance parameters. This perspective is characterized by the availability of a comprehensive set of long-term operational data on the one hand but the lack of detailed design information regarding the component characteristics of the operated gas turbine on the other hand. In the present study, the operational data set is provided by an E-class gas turbine that is operated in a Chinese combined cycle power plant. The physically based modelling approach used for this scenario is mainly based on a combination of heat- and mass balances representing a simplified thermodynamic gas turbine process. In addition, publicly available component maps are modified and subsequently integrated into the model. The corresponding data based modelling approach utilizes the set of long-term operational data as input parameters for the development of an artificial multi-layer perceptron neural network model with one hidden layer. The development steps conducted within the present study include the selection of adequate input and output parameters, the pre-processing of the data set for training and a sensitivity analysis regarding the number of neurons in the hidden layer. In summary, the results show that the data based model approach outperforms the physically based model approach based on an evaluation of the RMSE and the nRMSE. However, both the data based model approach and the physically based model approach are able to capture the main operational characteristics of the investigated gas turbine within the complete load range making both approaches suitable approach for long-term monitoring scenarios.

The HEC-6T one-dimensional numerical sedimentation model was used to evaluate the long-term and system-wide sedimentation effects of modifying the operation schedule at the Old River Control Complex (ORCC). The changes evaluated were increasing and decreasing the percentage of flow that is diverted to the Atchafalaya River from the Mississippi River at the ORCC and modifying the distributions through the four ORCC structures. Sedimentation effects for several operation scenarios were compared to a Base Condition that represented the existing operation protocols. Additionally, a dredging scenario was developed and analyzed. This scenario featured dredging material from the Mississippi River and depositing it into the Outflow Channel, downstream of the ORCC. The predictive simulations extended for 50 years. The model was used to calculate and compare sand transport past various gages along the Atchafalaya River. Also, the model compared differences in water surface elevations and bed elevations using a specific gage analysis at several gages along the Atchafalaya River. Last, the effects of the various scenarios on annual dredging requirements in Berwick Bay were also determined.

The Zanzibar Ministry of Education and Vocational Training (MoEVT) and the World Bank (the Bank) approached the EdTech Hub (the Hub) in April 2020 to explore the feasibility of implementing a Virtual Learning Environment (VLE). The Hub was requested to focus primarily on the deployment of a VLE in lower secondary education, and this report consequently focuses primarily on this group. The report is structured in four sections: An introduction to provide the background and guiding principles for the engagement with a short overview of the methodology applied. An analysis of the Zanzibar education system with a particular focus on elements relevant to deploying a VLE. This includes the status of ICT infrastructure, and a summary of the stakeholders who will play a role in using or implementing a VLE. A third section that discusses types of VLEs and content organisation, and their applicability to the Zanzibar ecosystem. A conclusion with recommendations for Zanzibar, including short- and long-term steps. In this collaboration with Zanzibar’s MoEVT, the Hub team sought to understand the purpose of the proposed VLE. Based on discussions and user scenarios, we identified two main education challenges a VLE may help to resolve. In the short term, students cannot go to school during the COVID-19 crisis, but need access to educational content. There is content, but no flexible and versatile platform to disseminate content to all students. In the long term, a mechanism to provide students with access to quality, curriculum-aligned content in school, or remotely, is required.

Many factors affect pavement compaction quality, which can vary. Such variability may result in an additional number of passes required, extended working hours, higher energy consumption, and negative environmental impacts. The use of Intelligent Compaction (IC) technology during construction can improve the quality and longevity of pavement structures while reducing risk for contractors and project owners alike. This study develops guidelines for the implementation of IC in the compaction of pavement layers as well as performing a preliminary life-cycle cost analysis (LCCA) of IC technology compared to the conventional compaction approach. The environmental impacts of the improved construction process were quantified based on limited data available from the case studies. The LCCA performed in this study consisted of different scenarios in which the number of operating hours was evaluated to estimate the cost efficiency of the intelligent compaction technique during construction. The analyses showed a reduction in energy consumption and the production of greenhouse gas (GHG) emissions with the use of intelligent compaction. The LCCA showed that the use of IC technology may reduce the construction and maintenance costs in addition to enhancing the quality control and quality assurance (QC/QA) process. However, a more comprehensive analysis is required to fully quantify the benefits and establish more accurate performance indicators. A draft version of the preliminary guidelines for implementation of IC technology and long-term monitoring of the performance of pavement layers compacted thereby is also included in this report.

This report analyzes anticipated list mile challenges in Indiana by using a scenario-based approach to develop forecasts of GDP growth and thus freight growth across industry clusters in Indiana counties; potential congestion implied by this growth; and a proactive plan to add capacity to alleviate the congestion. We use a quantitative approach to aggregate ramp level flows, industry cluster locations, county layout, and economic activity to develop our recommendations. We develop forecasts through the year 2050 based on long-term planning approaches used by other states (California, Ohio, and Utah). We use data from global databases that consider different possible geo-political scenarios and regulatory choices to scale it down to county-level impact. At the same time, we track industry cluster locations within each county, ramps from interstates, and distances to travel within the counties to reach freight destinations. The result is a report that combines macro trends with micro detail to develop potential capacity bottlenecks.

This report analyzes anticipated list mile challenges in Indiana by using a scenario-based approach to develop forecasts of GDP growth and thus freight growth across industry clusters in Indiana counties; potential congestion implied by this growth; and a proactive plan to add capacity to alleviate the congestion. We use a quantitative approach to aggregate ramp level flows, industry cluster locations, county layout, and economic activity to develop our recommendations. We develop forecasts through the year 2050 based on long-term planning approaches used by other states (California, Ohio, and Utah). We use data from global databases that consider different possible geo-political scenarios and regulatory choices to scale it down to county-level impact. At the same time, we track industry cluster locations within each county, ramps from interstates, and distances to travel within the counties to reach freight destinations. The result is a report that combines macro trends with micro detail to develop potential capacity bottlenecks.

Canada 1 Water is a 3-year governmental multi-department-private-sector-academic collaboration to model the groundwater-surface-water of Canada coupled with historic climate and climate scenario input. To address this challenge continental Canada has been allocated to one of 6 large watershed basins of approximately two million km2. The model domains are based on natural watershed boundaries and include approximately 1 million km2 of the United States. In year one (2020-2021) data assembly and validation of some 20 datasets (layers) is the focus of work along with conceptual model development. To support analysis of the entire water balance the modelling framework consists of three distinct components and modelling software. Land Surface modelling with the Community Land Model will support information needed for both the regional climate modelling using the Weather Research & Forecasting model (WRF), and input to HydroGeoSphere for groundwater-surface-water modelling. The inclusion of the transboundary watersheds will provide a first time assessment of water resources in this critical international domain. Modelling is also being integrated with Remote Sensing datasets, notably the Gravity Recovery and Climate Experiment (GRACE). GRACE supports regional scale watershed analysis of total water flux. GRACE along with terrestrial time-series data will serve provide validation datasets for model results to ensure that the final project outputs are representative and reliable. The project has an active engagement and collaborative effort underway to try and maximize the long-term benefit of the framework. Much of the supporting model datasets will be published under open access licence to support broad usage and integration.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

Banco de la República’s main objective is to preserve the purchasing power of the currency in coordination with the general economic policy that is intended to stabilize output and employment at long-term sustainable levels. Properly meeting the goal assigned to the Bank by the 1991 Constitution critically depends on preserving financial stability. This is understood to be a general condition in which the financial system assesses and manages the financial risks in a way that facilitates the economy’s performance and efficient allocation of resources while, at the same time, it is able to, on its own, absorb, dissipate, and mitigate the shocks that may arise as a result of adverse events. This Financial Stability Report meets the goal of giving Banco de la República’s diagnosis of the financial system’s and its debtors’ recent performance as well as of the main risks and vulnerabilities that could affect the stability of the Colombian economy. In this way, participants in financial markets and the public are being informed, and public debate on trends and risks affecting the system is being encouraged. The results presented here also serve the monetary authority as a basis for making decisions that will enhance financial stability in the general context of its objectives. In recent months, several positive aspects of the financial system have preserved a remarkable degree of continuity and stability: the liquidity and capital adequacy of financial institutions have remained well above the regulatory minimums at both the individual and consolidated levels, the coverage of past-due loans by loan-loss provisions remains high, and the financial markets for public and private debt and stocks have continued to function normally. At the same time, a surge in all the types of loan portfolios, a sharp downturn in the non-performing loan portfolio, and a rise in the profitability of credit institutions can be seen for the first time since the beginning of the pandemic. In line with the general recovery of the economy, the main vulnerability to the stability of the Colombian financial system identified in the previous edition—uncertainty about changes in the non-performing loans portfolio—has receded and remains on a downward trend. In this edition, the main source of vulnerability identified for financial stability in the short term is the system’s exposure to sudden changes in international financial conditions; the results presented in this Report indicate that the system is sufficiently resilient to such scenarios. In compliance with its constitutional objectives and in coordination with the financial system’s security network, Banco de la República will continue to closely monitor the outlook for financial stability at this juncture and will make the decisions necessary to ensure the proper functioning of the economy, facilitate the flow of sufficient credit and liquidity resources, and further the smooth functioning of the payment system. Leonardo Villar Gomez Governor Box 1 -Decomposition of the Net Interest Margin in Colombia and Chile Wilmar Cabrera Daniela Rodríguez-Novoa Box 2 - Spatial Analysis of New Home Prices in Bogota, Medellín, and Cali Using a Geostatistical Approach María Fernanda Meneses Camilo Eduardo Sánchez Box 3 - Interest Rate Model for the SYSMO Stress Test Exercise Wilmar Cabrera Diego Cuesta Santiago Gamba Camilo Gómez Box 4 - The Transition from LIBOR and other International Benchmark Rates Daniela X. Gualtero Briceño Javier E. Pirateque Niño

In the second quarter, annual inflation (9.67%), the technical staff’s projections and its expectations continued to increase, remaining above the target. International cost shocks, accentuated by Russia's invasion of Ukraine, have been more persistent than projected, thus contributing to higher inflation. The effects of indexation, higher than estimated excess demand, a tighter labor market, inflation expectations that continue to rise and currently exceed 3%, and the exchange rate pressures add to those described above. High core inflation measures as well as in the producer price index (PPI) across all baskets confirm a significant spread in price increases. Compared to estimates presented in April, the new forecast trajectory for headline and core inflation increased. This was partly the result of greater exchange rate pressure on prices, and a larger output gap, which is expected to remain positive for the remainder of 2022 and which is estimated to close towards yearend 2023. In addition, these trends take into account higher inflation rate indexation, more persistent above-target inflation expectations, a quickening of domestic fuel price increases due to the correction of lags versus the parity price and higher international oil price forecasts. The forecast supposes a good domestic supply of perishable foods, although it also considers that international prices of processed foods will remain high. In terms of the goods sub-basket, the end of the national health emergency implies a reversal of the value-added tax (VAT) refund applied to health and personal hygiene products, resulting in increases in the prices of these goods. Alternatively, the monetary policy adjustment process and the moderation of external shocks would help inflation and its expectations to begin to decrease over time and resume their alignment with the target. Thus, the new projection suggests that inflation could remain high for the second half of 2022, closing at 9.7%. However, it would begin to fall during 2023, closing the year at 5.7%. These forecasts are subject to significant uncertainty, especially regarding the future behavior of external cost shocks, the degree of indexation of nominal contracts and decisions made regarding the domestic price of fuels. Economic activity continues to outperform expectations, and the technical staff’s growth projections for 2022 have been revised upwards from 5% to 6.9%. The new forecasts suggest higher output levels that would continue to exceed the economy’s productive capacity for the remainder of 2022. Economic growth during the first quarter was above that estimated in April, while economic activity indicators for the second quarter suggest that the GDP could be expected to remain high, potentially above that of the first quarter. Domestic demand is expected to maintain a positive dynamic, in particular, due to the household consumption quarterly growth, as suggested by vehicle registrations, retail sales, credit card purchases and consumer loan disbursement figures. A slowdown in the machinery and equipment imports from the levels observed in March contrasts with the positive performance of sales and housing construction licenses, which indicates an investment level similar to that registered for the first three months of the year. International trade data suggests the trade deficit would be reduced as a consequence of import levels that would be lesser than those observed in the first quarter, and stable export levels. For the remainder of the year and 2023, a deceleration in consumption is expected from the high levels seen during the first half of the year, partially as a result of lower repressed demand, tighter domestic financial conditions and household available income deterioration due to increased inflation. Investment is expected to continue its slow recovery while remaining below pre-pandemic levels. The trade deficit is expected to tighten due to projected lower domestic demand dynamics, and high prices of oil and other basic goods exported by the country. Given the above, economic growth in the second quarter of 2022 would be 11.5%, and for 2022 and 2023 an annual growth of 6.9% and 1.1% is expected, respectively. Currently, and for the remainder of 2022, the output gap would be positive and greater than that estimated in April, and prices would be affected by demand pressures. These projections continue to be affected by significant uncertainty associated with global political tensions, the expected adjustment of monetary policy in developed countries, external demand behavior, changes in country risk outlook, and the future developments in domestic fiscal policy, among others. The high inflation levels and respective expectations, which exceed the target of the world's main central banks, largely explain the observed and anticipated increase in their monetary policy interest rates. This environment has tempered the growth forecast for external demand. Disruptions in value chains, rising international food and energy prices, and expansionary monetary and fiscal policies have contributed to the rise in inflation and above-target expectations seen by several of Colombia’s main trading partners. These cost and price shocks, heightened by the effects of Russia's invasion of Ukraine, have been more prevalent than expected and have taken place within a set of output and employment recovery, variables that in some countries currently equal or exceed their projected long-term levels. In response, the U.S. Federal Reserve accelerated the pace of the benchmark interest rate increase and rapidly reduced liquidity levels in the money market. Financial market actors expect this behavior to continue and, consequently, significantly increase their expectations of the average path of the Fed's benchmark interest rate. In this setting, the U.S. dollar appreciated versus the peso in the second quarter and emerging market risk measures increased, a behavior that intensified for Colombia. Given the aforementioned, for the remainder of 2022 and 2023, the Bank's technical staff increased the forecast trajectory for the Fed's interest rate and reduced the country's external demand growth forecast. The projected oil price was revised upward over the forecast horizon, specifically due to greater supply restrictions and the interruption of hydrocarbon trade between the European Union and Russia. Global geopolitical tensions, a tightening of monetary policy in developed economies, the increase in risk perception for emerging markets and the macroeconomic imbalances in the country explain the increase in the projected trajectory of the risk premium, its trend level and the neutral real interest rate1. Uncertainty about external forecasts and their consequent impact on the country's macroeconomic scenario remains high, given the unpredictable evolution of the conflict between Russia and Ukraine, geopolitical tensions, the degree of the global economic slowdown and the effect the response to recent outbreaks of the pandemic in some Asian countries may have on the world economy. This macroeconomic scenario that includes high inflation, inflation forecasts, and expectations above 3% and a positive output gap suggests the need for a contractionary monetary policy that mitigates the risk of the persistent unanchoring of inflation expectations. In contrast to the forecasts of the April report, the increase in the risk premium trend implies a higher neutral real interest rate and a greater prevailing monetary stimulus than previously estimated. For its part, domestic demand has been more dynamic, with a higher observed and expected output level that exceeds the economy’s productive capacity. The surprising accelerations in the headline and core inflation reflect stronger and more persistent external shocks, which, in combination with the strength of aggregate demand, indexation, higher inflation expectations and exchange rate pressures, explain the upward projected inflation trajectory at levels that exceed the target over the next two years. This is corroborated by the inflation expectations of economic analysts and those derived from the public debt market, which continued to climb and currently exceed 3%. All of the above increase the risk of unanchoring inflation expectations and could generate widespread indexation processes that may push inflation away from the target for longer. This new macroeconomic scenario suggests that the interest rate adjustment should continue towards a contractionary monetary policy landscape. 1.2. Monetary policy decision Banco de la República’s Board of Directors (BDBR), at its meetings in June and July 2022, decided to continue adjusting its monetary policy. At its June meeting, the BDBR decided to increase the monetary policy rate by 150 basis points (b.p.) and its July meeting by majority vote, on a 150 b.p. increase thereof at its July meeting. Consequently, the monetary policy interest rate currently stands at 9.0% . 1 The neutral real interest rate refers to the real interest rate level that is neither stimulative nor contractionary for aggregate demand and, therefore, does not generate pressures that lead to the close of the output gap. In a small, open economy like Colombia, this rate depends on the external neutral real interest rate, medium-term components of the country risk premium, and expected depreciation. Box 1: A Weekly Indicator of Economic Activity for Colombia Juan Pablo Cote Carlos Daniel Rojas Nicol Rodriguez Box 2: Common Inflationary Trends in Colombia Carlos D. Rojas-Martínez Nicolás Martínez-Cortés Franky Juliano Galeano-Ramírez Box 3: Shock Decomposition of 2021 Forecast Errors Nicolás Moreno Arias