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Ecuador is a country with several climate zones. However, their behaviour is similar throughout the year, with no peaks of extreme temperatures in the various seasons. This paper is a first approach to study the adaptive comfort behaviour in several areas and populations of the country. Considering the ASHRAE 55-2020 model, energy simulation programmes are applied not just to the current climate scenario but also to the climate change scenarios of 2050 and 2100. The results of locations are analysed and compared to determine their performance. Thanks to their climate characteristics, adaptive comfort models could be applied as a passive strategy, using natural ventilation for building indoor comfort improvement, particularly social dwellings. According to previous studies, some prototypes have not considered the climate determinants in each region. Given the geographic situation of the study areas, the adaptive comfort model could be applied in all cases. Percentages of application of natural ventilation and heating and cooling degree hours have similar behaviours according to the climatic region, with a variation greater than 30% among them. [ABSTRACT FROM AUTHOR]

Increasingly people, especially those residing in urban areas with the urban heat island effect, are getting exposed to extreme heat due to ongoing global warming. A number of methods have been developed, so far, to assess urban heat vulnerability in different locations across the world concentrating on diverse aspects of these methods. While there is growing literature, thorough review studies that compare, contrast, and help understand the prospects and constraints of urban heat vulnerability assessment methods are scarce. This paper aims to bridge this gap in the literature. A systematic literature review with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach is utilized as the methodological approach. PRISMA is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. The results are analyzed in three aspects—i.e., indicators and data, modelling approaches, and validation approaches. The main findings disclose that: (a) Three types of indicators are commonly used—i.e., demographic properties and socioeconomic status, health conditions and medical resources, and natural and built environmental factors; (b) Heat vulnerability indexing models, equal weighting method, and principal component analysis are commonly used in modelling and weighting approaches; (c) Statistical regressions and correlation coefficients between heat vulnerability results and adverse health outcomes are commonly used in validation approaches, but the performance varies across studies. This study informs urban policy and generates directions for prospective research and more accurate vulnerability assessment method development. [ABSTRACT FROM AUTHOR]

To avoid the potential adverse impacts of climate change from global warming, it is suggested that the target of net zero emissions should be reached by this mid-century. Thailand is aiming to achieve carbon neutrality by 2050. Since electricity generation is one of the largest producers of carbon dioxide emission, the associated emissions must be greatly reduced to achieve the targets mentioned above. Thus, new generation expansion plans must be well developed. This paper discusses the development of generation expansion plans considering Thailand's latest policies along with enhancement of the existing multi-period linear programming model, allowing new electricity generation technologies having low emissions, e.g., solar PV with battery and hydrogen blending in natural gas, to be integrated into generation expansion planning. Then, four generation expansion plans with different levels of hydrogen blending in natural gas are proposed and discussed. It is found that Thailand can achieve carbon neutrality by 2050 by promoting more use of renewable energy altogether with trade-off between land for solar PV installation and amount of hydrogen blended in natural gas. The lesson learned from this study provides crucial information about possible pathways to achieve carbon neutrality in the electricity sector for policy makers in other countries. [ABSTRACT FROM AUTHOR]

Energy is crucial to economic progress, but the contemporary worldwide population increase that demands greater energy generated from conventional exhaustible resources, an energy price upsurge, and environmental concerns, imperils sustainable economic growth. Nevertheless, switching to renewable energy produced from naturally replenished resources promotes energy security, likewise addressing issues such as global warming and climate change. This paper aims at exploring the influence and causal relation between renewable energy, both overall and by type, and sustainable economic growth of European Union (EU)-28 countries for the period of 2003-2014. We notice that the mean share of renewable energy in the gross final energy consumption is 15%, while the mean share of renewable energy in transport fuel consumption is 3%, which are below the thresholds of 20% and 10%, respectively, as set by the EU Directive 2009/28/EC. By estimating panel data fixed-effects regression models, the results provide support for a positive influence of renewable energy overall, as well as by type, namely biomass, hydropower, geothermal energy, wind power, and solar energy on gross domestic product per capita. However, biomass energy shows the highest influence on economic growth among the rest of renewable energy types. In fact, a 1% increase of the primary production of solid biofuels increases GDP per capita by 0.16%. Besides, cointegrating regressions set on panel fully modified and dynamic ordinary least squares regressions confirm the positive influence related to the primary production of renewable energies on economic growth. A 1% increase in primary production of renewable energies increases GDP per capita by 0.05%-0.06%. However, the results of Granger causality based on panel vector error correction model indicate both in short-run and long-run a unidirectional causal relationship running from sustainable economic growth to the primary production of renewable energies, being supported the conservation hypothesis. [ABSTRACT FROM AUTHOR]

For some time, there has been a slow but gradual rise in the average temperature of the entire globe, a "global warming", in fact, the result of human and natural processes that have been producing this phenomenon for decades. Since they are not directly perceived by individuals, these processes and their effects have been ignored for a long time, or at least not considered to be immediately harmful and dangerous. Global warming does not depend so much on solar radiation as it does on the greenhouse effect deriving from the continuous emission, by human activities and natural events, of greenhouse gases that accumulate in the atmosphere and form a barrier to the dispersion of heat produced by solar radiation. A good number of models exists to explain how global warming is produced, which are technical in nature and consider the production of greenhouse gases as the most important cause; however, they do not always analyze and justify the reasons for such emissions. Following the logic, language and methods of Senge's systems thinking, the paper aims to present a general model, the GEAM—qualitative in nature, but rational and coherent—for highlighting the interacting factors that give rise to and maintain global warming. This model constitutes a reference framework to identify possible "strategic areas" within which to identify man-made "artificial" and "natural" factors that can control the phenomenon and to order the countless ideas and interventions that different nations carry out individually to control global warming. The model presented is qualitative in nature and does not allow immediate calculations or forecasts to be performed. However, it could guide in-depth scientific research in generating accurate forecasts and simulation using the tools of systems dynamics. In conclusion, understanding how global warming is created and if and how it could be controlled is the aim of this work. Finally, I want to note that the purpose of this work is not to analyze the technical aspects of the phenomenon of global warming, or to deepen the measures and actions to contrast it, but to provide a "general model of description and understanding" of the phenomenon using logic and language of the Systems Thinking Approach (according to Peter's Senge and Piero Mella), with the aim of highlighting three fundamental strategic areas for countering the phenomenon and four uncontrollable phenomena, triggered by global warming itself, which can make strategic control difficult. Furthermore, I highlight the role played by the world population, understood both quantitatively as a number and qualitatively as a level of economic development, in the production of global warming. Lastly, I observe how the different strategic actions that nations can, indeed must, implement to stem global warming are systematically interconnected and interacting; however, these interactions can produce unknown effects and consequences that must be carefully researched and evaluated—encouraged, if positive, reduced or eliminated if negative. [ABSTRACT FROM AUTHOR]

Wind power has been increasing its participation in electricity markets in many countries around the world. Due to its economical and environmental benefits, wind power generation is one of the most powerful technologies to deal with global warming and climate change. However, as wind power grows, uncertainty in power supply increases due to wind intermittence. In this context, accurate wind power scenarios are needed to guide decision-making in power systems. In this paper, a novel methodology to generate realistic wind power scenarios for the long term is proposed. Unlike most of the literature that tackles this problem, this paper is focused on the generation of realistic wind power production scenarios in the long term. Moreover, spatial-temporal dependencies in multi-area markets have been considered. The results show that capturing the dependencies at the monthly level could improve the quality of scenarios at different time scales. In addition, an evaluation at different time scales is needed to select the best approach in terms of the distribution functions of the generated scenarios. To evaluate the proposed methodology, several tests have been made using real data of wind power generation for Spain, Portugal and France. [ABSTRACT FROM AUTHOR]

In today's energy system, the diffusion of renewable-based technologies is accelerating rapidly. Development of mechanisms that support the large-scale deployment of renewables towards global warming and climate change mitigation continues to remain an issue of utter importance. The most important challenges the energy system of Kosovo faces today is the difficulty to meet all the demand for electricity, low operating efficiency and high release of greenhouse gas emissions, but specifically a large source of carbon dioxide (CO2). Consequently, this influences not only the stability of the system but the society as a whole. This paper addresses several possibilities for designing an adaptable energy system in Kosovo with the ability to balance electricity supply and demand which will meet the requirements for a more efficient, reliable and secure system. A new way of energy generating through integration of new renewable and non-renewable technologies is developed using the EnergyPLAN model. The system is based on available technologies: existing hydro, wind, photovoltaic (PV), combined heat and power (CHP) and new solar thermal, heat pumps and biomass. The baseline scenario 2015 was expanded by four additional scenarios, two for the year 2030 and two for the year 2050. The contribution of renewable sources in the primary energy supply (PES) in the performed scenarios was 14.8%, 34.1%, 38.4%, 69.7% and 68.3% respectively. Further, a very important component of this paper is the investigation of integrating carbon capture and sequestration (CCS) technology in the coal-based power plant as part of the analysis in the second scenario for 2050. The shift to zero-carbon energy system in Kosovo requires additional research and assessment in order to identify the untapped potential of renewable sources. However, from the results obtained it can be concluded that the goal of a secure, competitive and sustainable energy system in Kosovo state which will meet its long-term energy needs can be certainly achieved. [ABSTRACT FROM AUTHOR]

Overheating in residential building is a challenging problem that causes thermal discomfort, productivity reduction, and health problems. This paper aims to assess the climate change impact on thermal comfort in a Belgian reference case. The case study represents a nearly zero energy building that operates without active cooling during summer. The study quantifies the impact of climate change on overheating risks using three representative concentration pathway (RCP) trajectories for greenhouse gas concentration adopted by the Intergovernmental Panel on Climate Change (IPCC). Building performance analysis is carried out using a multizone dynamic simulation program EnergyPlus. The results show that bioclimatic and thermal adaptation strategies, including adaptive thermal comfort models, cannot suppress the effect of global warming. By 2050, zero energy buildings will be vulnerable to overheating. [ABSTRACT FROM AUTHOR]

It is generally accepted in the scientific community that carbon dioxide (CO2) emissions, which lead to global warming, arise from using fossil fuels, namely coal, oil and gas, as energy sources. Consequently, alleviating the effects of global warming and climate change necessitates substantial reductions in the use of fossil fuel energy. This paper uses a financial market-based approach to investigate whether positive stock returns cause changes in CO2 emissions, or vice-versa, based on the Granger causality test to determine cause and effect, or leader and follower. If Granger causality can be determined in any direction, this will enable a clear directional statement regarding temporal predictability between stock returns and CO2 emissions. The empirical data include annual CO2 emissions from fuel combustion of the three main fossil energy sources, namely coal, oil and gas, based on 18 countries with sophisticated financial markets that are in the Morgan Stanley Capital International (MSCI) World Index from 1971 to 2017. The empirical results show clearly that all the statistically significant causality findings are unidirectional from the stock market returns to CO2 emissions from coal, oil and gas, but not the reverse. More importantly, the regression results suggest that when stock returns rise by 1%, CO2 emissions from coal combustion decrease by 9% among the countries that are included in MSCI World Index. Furthermore, when stock returns rise 1%, CO2 emissions from oil combustion increase by 2%, but stock returns have no significant effect on CO2 emissions from gas combustion. [ABSTRACT FROM AUTHOR]

Climate change is around us today and will affect human life in many ways. More frequent extreme weather events raise mortality and car accident rates, global warming leads to longer growing seasons for crops, which may change farmers' crop choices, and the relationship between energy demand in residential buildings and weather is widely investigated. In this paper, we focus on the impact of weather on energy consumption, in particular, gasoline consumption through the more frequent use of both vehicles themselves and the air conditioner of the vehicle that decreases fuel economy, which has not been paid enough attention in the literature. We estimate the relationship between fuel consumption and weather using unique U.S. panel data. We find that hot days increase gasoline consumption, but in contrast to the results of residential energy consumption literature, there is no statistically significant effect on cold weather. With climate prediction data from General Circulation Models (GCMs), we simulate the impact of climate change on fuel energy consumption. The results show that the fuel consumption in the transportation sector may increase by up to 4% under the "business-as-usual" (RCP 8.5) scenario. Also, climate change has heterogeneous impacts across the continental United States. [ABSTRACT FROM AUTHOR]

This paper tests the validity of the FUND model's energy impact functions, and the hypothesis that global warming of 2 °C or more above pre-industrial times would negatively impact the global economy. Empirical data of energy expenditure and average temperatures of the US states and census divisions are compared with projections using the energy impact functions with non-temperature drivers held constant at their 2010 values. The empirical data indicates that energy expenditure decreases as temperatures increase, suggesting that global warming, by itself, may reduce US energy expenditure and thereby have a positive impact on US economic growth. These findings are then compared with FUND energy impact projections for the world at 3 °C of global warming from 2000. The comparisons suggest that warming, by itself, may reduce global energy consumption. If these findings are correct, and if FUND projections for the non-energy impact sectors are valid, 3 °C of global warming from 2000 would increase global economic growth. In this case, the hypothesis is false and policies to reduce global warming are detrimental to the global economy. We recommend the FUND energy impact functions be modified and recalibrated against best available empirical data. Our analysis and conclusions warrant further investigation. [ABSTRACT FROM AUTHOR]

The Climate Change scenario projected by the IPCC for the year 2050 predicts noticeable increases in temperature. In severe summer climates, such as the Mediterranean area, this would have very negative effects on thermal comfort in the existing housing stock, given the current high percentage of dwellings which are obsolete in energy terms and house a population at serious risk of energy poverty. The main aim of this paper is to generate a predictive model in order to assess the impact of this future climate scenario on thermal comfort conditions in an entire building category. To do so, calibrated models representing linear-type social multi-family buildings, dating from the post-war period and located in southern Spain, will be simulated extensively using transient energy analyses performed by EnergyPlus. In addition, a sensitivity analysis will be performed to identify the most influential parameters on thermal discomfort. The main results predict a generalized deterioration in indoor thermal comfort conditions due to global warming, increasing the average percentage of discomfort hours during the summer by more than 35%. This characterization of the future thermal behaviour of the residential stock in southern Spain could be a trustworthy tool for decision-making in energy retrofitting projects which are so badly needed. To do so, further work is required on some limitations of this model so that different user profiles and typologies can be represented in detail and an economic assessment can be included. [ABSTRACT FROM AUTHOR]

Solar energy harvesting using Photovoltaic (PV) systems is one of the most popular sources of renewable energy, however the main drawback of PV systems is their low conversion efficiency. An optimal system operation requires an efficient tracking of the Maximum Power Point (MPP), which represents the maximum energy that can be extracted from the PV panel. This paper presents a novel control approach for the Maximum Power Point Tracking (MPPT) based on the differential flatness property of the Boost converter, which is one of the most used converters in PV systems. The underlying idea of the proposed control approach is to use the classical flatness-based trajectory tracking control where a reference voltage will be defined in terms of the maximum power provided by the PV panel. The effectiveness of the proposed controller is assessed through numerical simulations and experimental tests. The results show that the controller based on differential flatness is capable of converging in less than 0.15 s and, compared with other MPPT techniques, such as Incremental Conductance and Perturb and Observe, it improves the response against sudden changes in load or weather conditions, reducing the ringing in the output of the system. Based on the results, it can be inferred that the new flatness-based controller represents an alternative to improve the MPPT in PV systems, especially when they are subject to sudden load or weather changes. [ABSTRACT FROM AUTHOR]