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Global fossil fuel reserves are declining due to differential uses, especially for power generation. Everybody can help to do their bit for the environment by using solar energy. Geographically, Bangladesh is a potential zone for harnessing solar energy. In March 2021, the renewable generation capacity in Bangladesh amounted to 722.592 MW, including 67.6% from solar, 31.84% from hydro, and 0.55% from other energy sources, including wind, biogas, and biomass, where 488.662 MW of power originated from over 6 million installed solar power systems. Concurrently, over 42% of rural people still suffer from a lack of electricity, where solar energy can play a vital role. This paper highlights the present status of various forms of solar energy progress in Bangladesh, such as solar parks, solar rooftops, solar irrigation, solar charging stations, solar home systems, solar-powered telecoms, solar street lights, and solar drinking water, which can be viable alternative sources of energy. This review will help decision-makers and investors realize Bangladesh’s up-to-date solar energy scenario and plan better for the development of a sustainable society.

Abstract Two office layouts with high and low levels of thermal control were compared, respectively traditional cellular and contemporary open plan offices. The traditional Norwegian practice provided every user with control over a window, blinds, door, and the ability to adjust heating and cooling. Occupants were expected to control their thermal environment to find their own comfort, while air conditioning was operating in the background to ensure the indoor air quality. In contrast, in the British open plan office, limited thermal control was provided through openable windows and blinds only for occupants seated around the perimeter of the building. Centrally operated displacement ventilation was the main thermal control system. Users’ perception of thermal environment was recorded through survey questionnaires, empirical building performance through environmental measurements and thermal control through semi-structured interviews. The Norwegian office had 35% higher user satisfaction and 20% higher user comfort compared to the British open plan office. However, the energy consumption in the British practice was within the benchmark and much lower than the Norwegian office. Overall, a balance between thermal comfort and energy efficiency is required, as either extreme poses difficulties for the other.

Abstract The Renewable energy power generation capacity has been rapidly increasing in China recently. Meanwhile, the contradiction between power supply and demand is becoming increasingly more prominent due to the intermittence of renewable energies. On the other hand, on the mitigation of carbon dioxide (CO2) emissions in China needs immediate attention. Power-to-Gas (PtG), a chemical energy storage technology, can convert surplus electricity into combustible gases. Subsurface energy storage can meet the requirements of long term storage with its large capacity. This paper provides a discussion of the entire PtG energy storage technology process and the current research progress. Based on the comparative study of different geological storage schemes for synthetic methane, their respective research progress and limitations are noted. In addition, a full investigation of the distribution and implementation of global PtG and CO2 capture and storage (CCS) demonstration projects is performed. Subsequently, the opportunities and challenges of the development of this technology in China are discussed based on techno-economic and ecological effects analysis. While PtG is expected to be a revolutionary technology that will replace traditional power systems, the main issues of site selection, energy efficiency and the economy still need to be adequately addressed. Additionally, based on the comprehensive discussion of the results of the analysis, power-to-gas and subsurface energy storage implementation strategies, as well as outlook in China are presented.

Abstract In developed countries, buildings are involved in almost 50% of total energy use and 30% of global green-house gas emissions. Buildings' operational energy is highly dependent on various building physical, operational, and functional characteristics, as well as meteorological and temporal properties. Besides physics-based building energy modeling, machine learning techniques can provide faster and higher accuracy estimates, given buildings' historic energy consumption data. Looking beyond individual building levels, forecasting buildings’ energy performance helps city and community managers have a better understanding of their future energy needs, and plan for satisfying them more efficiently. Focusing on an urban-scale, this study systematically reviews 70 journal articles, published in the field of building energy performance forecasting between 2015 and 2018. The recent literature have been categorized according to five criteria: 1. Learning Method, 2. Building Type, 3. Energy Type, 4. Input Data, and 5. Time-scale. The scarcity of building energy performance forecasting studies in urban-scale versus individual level is considerable. There is no study incorporating building functionality in terms of space functionality share percentages, nor assessing the effects of climate change on urban buildings energy performance using machine learning approaches and future weather scenarios. There is no optimal criteria combination for achieving the most accurate machine learning-based forecast, as there is no universal measure able to provide such global comparison. Accuracy levels are highly correlated with the characteristics of forecasting problems. The goal is to provide a comprehensive status of machine learning applications in urban building energy performance forecasting, during 2015–2018.

Abstract Kenya has made considerable policy efforts to expand its renewable energy portfolio to meet energy demand and mitigate greenhouse gas (GHG) emissions. Development of proper policies requires a robust framework for analyzing the benefits of renewable energy investments. Towards this end, this study applied a choice experiment analysis to determine how attributes (type of energy, ownership, impact on environment, distance and visibility, community job creation, and yearly renewable energy tax) impact the public willingness to pay for renewable energy development in Kenya. A nationwide survey of 1020 households was conducted in nine counties using conditional logit (MNL) and random parameter logit (RPL) frameworks. The results reveal that the Kenyan public places a high value on environmental impact, followed by type of renewable energy and community job creation, respectively. On the other hand, respondents do not place much emphasis on ownership or distance and visibility. Policy simulation suggests that while renewable energy adoption is highly valued by households, the total willingness to pay is not enough to cover the higher capital cost for the development of various renewable energy technologies.

The failure to fully internalize externalities from production and consumption, including on future generations, is supposed to be at the core of the perceived failure to ensure (ecological) sustainability within the realm of antitrust enforcement. While some argue that sustainability should constitute a goal in itself that must be balanced against economic efficiency in antitrust analysis, we instead want to explore whether and how sustainability can be incorporated into a consumer welfare approach. We make a key distinction between what we term an individualistic and a collective consumer welfare analysis. Within an individualistic consumer welfare analysis, consumers’ willingness-to-pay is measured ceteris paribus, holding other consumers’ choices fixed. In a collective consumer welfare analysis, consumers may express their willingness-to-pay also for the choices of others and, thereby, also for the reduction of externalities on themselves. Borrowing from environmental and resource economics, we also discuss more indirect ways of incorporating such externalities. And we critically assess the possibility of ‘laundering’ consumers’ sustainability preferences in the light of supposed biases and cognitive limitations. Finally, we relate our analysis to the Draft Horizontal Guidelines of the European Commission, published in March 2022. antitrust, consumer welfare, conjoint analysis, contingent valuation, Draft EU Horizontal Guidelines, environmental economics, externalities, laundering preferences, sustainability, willingness-to-pay

Integrated assessment models (IAMs) are playing an increasingly important role in long-run sustainability analysis. At their core is a set of global economic and environmental accounts which capture a complete set of inter-industry and inter-regional relationships in the global economy in a consistent manner. While much attention is focused on the raw data and parameterization required to expand or add sectoral detail to IAMs, only rarely is there discussion of how different matrix balancing methods (i.e. translating disparate raw data sources into the consistent database) affect modeling results. This article offers an in-depth look into the database–modeling nexus in IAMs, focusing on the electric power sector which is both a major source of CO2 emissions and a critical vehicle for climate change mitigation. Comparisons of the prevailing matrix balancing algorithms show how the choice of database reconciliation methodology affects modeling results using policy-relevant simulations in the context of the electric power sector. The resulting insights can be applied to the disaggregation of other, technology rich sectors in the economy. We conclude that appropriate selection of database reconciliation methodologies can reduce the deviation between bottom-up and top-down modeling.

Abstract Real-world vehicle operating mode data (2.5 million 1 Hz records), collected by instrumenting the vehicles of 82 volunteer drivers with OBD datalogger and GPS while they drove their routine travel routes, were analyzed to quantify vehicle emissions estimate errors due to road grade and driving style in rural, hilly Vermont. Data were collected in winter and summer for MY 1996 and newer passenger cars and trucks only. EPA MOVES2010b was used to estimate running exhaust emissions associated with measured vehicle activity. Changes in vehicle specific power (VSP) and MOVES operating mode (OpMode) due to proper accounting for real-world road grade indicated emission rate errors between 10% and 48%, depending on pollutant, chiefly because grade-related changes in VSP could shift activity by as many as six OpModes, depending on road type. The correct MOVES OpMode assignment was made only 33–55% of the time when road grade was not included in the VSP calculation. Driving style of individual drivers was difficult to assess due to unknown traffic operations data, but the largest differences between individual drivers were observed on rural restricted roads, where traffic conditions and control have minimal impact. The results suggest the importance of (1) measuring and incorporating real-world road grade in order to correctly assign MOVES emission rates; and (2) developing a driving style typology to account for differences in the MOVES emissions estimates due to driver variability.

Carbon capture and utilization (CCU) is a field of key emerging technologies. CCU can support the economy to decrease the dependency on fossil carbon raw materials, to stabilize electricity grids and markets with respect to a growing share of fluctuating renewable energy. Furthermore, it can contribute to mitigate anthropogenic CO2 emissions. The German Federal Ministry of Education and Research has provided substantial financial support for research and development projects, stimulating research, development, and innovations in the field of CO2 utilization. This review provides an overview over the most relevant funding measures in this field. Examples of successful projects demonstrate that CCU technologies are already economically viable or technologically ready for industrial application. CCU technologies as elements of a future "green economy" can contribute to reach the ambitious German sustainability targets with regard to climate protection as well as raw material productivity.