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As a relatively mature technology, biomass molded fuel (BMF) is widely used in distributed and centralized heating in China and has received considerable government attention. Although many BFM incentive policies have been developed, decreased domestic traditional fuel prices in China have caused BMF to lose its economic viability and new policy recommendations are needed to stimulate this industry. The present study built a regionalized net present value (NPV) model based on real production process simulation to test the impacts of each policy factor. The calculations showed that BMF production costs vary remarkably between regions, with the cost of agricultural briquette fuel (ABF) ranging from 86 US dollar per metric ton (USD/t) to 110 (USD/t), while that of woody pellet fuel (WPF) varies from 122 USD/t to 154 USD/t. The largest part of BMF’s cost composition is feedstock, which accounts for up 50%–60% of the total; accordingly a feedstock subsidy is the most effective policy factor, but in consideration of policy implementation, it would be better to use a production subsidy. For ABF, the optimal product subsidy varies from 26 USD/t to 57 USD/t among different regions of China, while for WPF, the range is 36 USD/t to 75 USD/t. Based on the data, a regional BMF development strategy is also proposed in this study.

Car-sharing services are developing at an ever-increasing pace. Taking into account the reduction of carbon dioxide emissions and pursuit of the sustainable development of transport, implementing electric cars in car-sharing fleets is being proposed. On the one hand, these types of vehicles are referred to as emission-free, but on the other hand, their environmental friendliness is questionable due to the emission of carbon dioxide during the production of energy to power them. Although many scientific papers are devoted to the issue of reducing emissions through car sharing, there is a research gap concerning the real production of carbon dioxide by car-sharing vehicles during car-sharing trips. To fill this research gap, the objective of the article was to analyze the actual level of carbon dioxide emissions from combustion and electric vehicles from car-sharing systems produced when renting rides. The test results showed that the electric car turned out to be significantly less emitting. The use of electric vehicles in car-sharing fleets can reduce carbon dioxide emissions from 14% to 65% compared to using cars with internal combustion engines. However, the key role during car-sharing trips is played by the driving style of the drivers, which has been omitted from the literature to date. This should be properly regulated by service providers and focus on the proper use of energy from electric vehicle batteries, especially at low temperatures. The article provides support for operators planning to modernize their fleet of vehicles and fills the research gap concerning car-sharing emissions.

The decarbonisation of heating in the United Kingdom is likely to entail both the mass adoption of heat pumps and widespread development of district heating infrastructure. Estimation of the spatially disaggregated heat demand is needed for both electrical distribution network with electrified heating and for the development of district heating. The temporal variation of heat demand is important when considering the operation of district heating, thermal energy storage and electrical grid storage. The difference between the national and urban heat demands profiles will vary due to the type and occupancy of buildings leading to temporal variations which have not been widely surveyed. This paper develops a high-resolution spatiotemporal heat load model for Great Britain (GB: England, Scotland a Wales) by identifying the appropriate datasets, archetype segmentation and characterisation for the domestic and nondomestic building stock. This is applied to a thermal model and calibrated on the local scale using gas consumption statistics. The annual GB heat demand was in close agreement with other estimates and the peak demand was 219 GWth. The urban heat demand was found to have a lower peak to trough ratio than the average national demand profile. This will have important implications for the uptake of heating technologies and design of district heating.

One of the repeating themes around the provision of the knowledge and skills needed for delivering sustainable communities is the idea of a “common language” for all built environment professionals. This suggestion has been repeated regularly with each new political and professional review within and between different sectors responsible for the delivery of sustainable communities. There have been multiple efforts to address academic limitations, industry fragmentation and promote more interdisciplinary working and sector collaboration. This research explored the role of skills for sustainable communities, particularly within the higher education (HE) sector, and the responses to support the development of a “common language of sustainability” that can be shared between different sectors, professional disciplines and stakeholders. As an interdisciplinary group of academics and practitioners working with the HE sector in the North East of England, we evaluate the progression of sector collaboration to develop a quintuple helix model for HE. We use this as a suitable framework for systematically “mapping” out the mixed sector (academic, public, business, community and environmental organisations) inputs and influences into a representative sample of HE degree modules that are delivered from foundation and undergraduate to postgraduate levels, including examples of part-time and distance-learning modules. We developed a cascade of models which demonstrate increasing levels of collaboration and their potential positive impact on the effectiveness of education on sustainable communities. The methodological assessments of modules were followed by semi-structured group reflective analysis undertaken through a series of online workshops (recorded during the Covid19 lockdown) to set out a collective understanding of the generic skills needed for the delivery of sustainable communities. These generic skills for sustainable communities are presented as a pedagogical progression model of teaching activities and learning outcomes applied to the levels within HE. We propose sustainability education principles and progressions with the hope that they can have an impact on the design or review of current degree modules and programmes. The paper informs future sustainability research to be grounded in holism and systems thinking; better understanding of values, ethics, influencing and political impact; and procedural authenticity.

In this paper, the author intends to show the interaction between the living standards of the population and the financial situation of Polish local government units at the commune level. The first (theoretical) part of the paper provides a synthetic description of topics related to defining the economic terms and to the local government’s ability to impact the standards of living of the local population. In view of the multifaceted nature of terms covered by this analysis, the second part uses a canonical analysis (which means multiple linear regressions are generalized for two sets of variables) in order to identify the relationships between them. The analysis resulted in identifying a number of indicators, including canonical correlations, total redundancy and variances extracted, as well as six statistically significant canonical variates, which enabled the identification of multidimensional relationships between the categories considered. The greatest and the most statistically significant canonical correlation coefficient was over 0.93; for the last statistically significant canonical variate, it was over 0.57. The analysis provides grounds for concluding that when the values of variables representing the financial capacity of Polish rural communes are known, they can be used to explain over 32% of the variance in the set of variables relating to the population’s standards of living. The statistical data originated from the author’s own surveys carried out with presidents and vice-presidents of commune councils.

In China, the power sector is currently the largest carbon emitter and the transportation sector is the fastest-growing carbon emitter. This paper proposes a model of solar-powered charging stations for electric vehicles to mitigate problems encountered in China’s renewable energy utilization processes and to cope with the increasing power demand by electric vehicles for the near future. This study applies the proposed model to Shenzhen City to verify its technical and economic feasibility. Modeling results showed that the total net present value of a photovoltaic power charging station that meets the daily electricity demand of 4500 kWh is $3,579,236 and that the cost of energy of the combined energy system is $0.098/kWh. In addition, the photovoltaic powered electric vehicle model has pollutant reduction potentials of 99.8%, 99.7% and 100% for carbon dioxide, sulfur dioxide, and nitrogen oxides, respectively, compared with a traditional gasoline-fueled car. Sensitivity analysis results indicated that interest rate has a relatively strong influence on COE (Cost of Energy). An increase in the interest rate from 0% to 6% increases COE from $0.027/kWh to $0.097/kWh. This analysis also suggests that carbon pricing promotes renewable energy only when the price of carbon is above $20/t.

This paper proposes the computation and assessment of optimal tilt and azimuth angles for a receiving surface, using a mathematical model developed at the University of Tomsk, Russia. The model was validated and analyzed for the Nuevo León State, Northeast Mexico, utilizing a set of metrics, comparing against satellite data from NASA. A point of interest in the city of Monterrey was analyzed to identify orientation patterns throughout the year for an optimal solar energy gathering. The aim is providing the best orientation tilt angles for photovoltaic or solar thermal panels without tracking systems. In addition, this analysis is proposed as a tool to achieve optimal performance in sustainable urban development in the region. Based on the findings, a set of optimal tilt and azimuth surface angles are proposed for the analyzed coordinates. The aim is to identify the optimal performance to obtain the maximum solar irradiation possible over the year for solar projects in the region. The results show that the model can be used as a tool to accelerate decision making in the design of solar harvesting surfaces and allows the design of discrete tracking systems with an increase in solar energy harvesting above 5% annually.

The growing number of electric vehicles in recent years is observable in almost all countries. The country’s energy transition should accompany this rise in electromobility if it is currently generated from non-renewable sources. Only electric vehicles powered by renewable energy sources can be considered zero-emission. Therefore, it is essential to conduct interdisciplinary research on the feasibility of combining energy recovery/generation structures and testing the energy consumption of electric vehicles under real driving conditions. This work presents a comprehensive approach for evaluating the energy consumption of a modern public building–electric vehicle system within a specific location. The original methodology developed includes surveys that demonstrate the required mobility range to be provided to occupants of the building under consideration. In the next step, an energy balance was performed for a novel near-zero energy building equipped with a 199.8 kWp photovoltaic installation, the energy from which can be used to charge an electric vehicle. The analysis considered the variation in vehicle energy consumption by season (winter/summer), the actual charging profile of the vehicle, and the parking periods required to achieve the target range for the user.

Various problems often arise in high-rise buildings during the winter months due to the stack effect. In this study, the high-rise building of interest, located in South Korea, was experiencing constant loud noises in the winter due to the stack effect. Thus, we created a noise level reduction plan by creating a method for pressurizing the high-rise zones of the building according to outdoor conditions. To discover the appropriate pressurization operating modes, we applied a two-year commissioning process to the 50-story building of interest. The 1st- and 47th-floor elevator halls were identified to have the highest noise levels of all other floors. Prior to applying the reduction plan, the maximum noise level on the first floor with the HVAC system turned off was 85 dB(A) and with the HVAC system turned on it was 70 dB(A). Both values exceeded the criteria of 57 dB(A) for a lobby space of a commercial building. In the case of the 47th floor, the maximum noise level with the HVAC system turned off was 58.7 dB(A) and with the HVAC system turned off was 56.0 dB(A), despite the latter having increased airtightness performance and applying preliminary pressurization (i.e., HVAC operation mode 2). These values exceeded the criteria of 48 dB(A) for an elevator hall in a commercial building. Following this initial data, we determined to pressurize the high/mid-rise zones of the building according to the outdoor air temperature and wind velocity conditions, which we categorized into four types (i.e., HVAC operation mode 4). To this effect, the first-floor elevator hall’s maximum noise level was 56.6 dB(A), meeting the criteria, and the 47th-floor elevator hall’s maximum noise level was 49.5 dB(A), still exceeding the criteria but by an insignificant amount. Although the HVAC pressurization operation we utilized resulted in favorable results for the target building A, it may not be as effective in other new high-rise buildings, creating changes to the indoor air environment or to the energy costs in maintaining a building. However, for the purposes of resolving the stack effect, we believe that the commissioning process we took to optimize the HVAC operation that is presented here can be applied to other new and existing high-rise commercial buildings.

Mobile Global Navigation Satellite System (GNSS) measurements carried out on the railway consist of using satellite navigation systems to determine the track geometry of a moving railway vehicle on a given route. Their purposes include diagnostics, stocktaking, and design work in railways. The greatest advantage of this method is the ability to perform measurements in a unified and coherent spatial reference system, which effectively enables the combining of design and construction works, as well as their implementation by engineering teams of diverse specialties. In the article, we attempted to assess the impact of using three types of work mode for a GNSS geodetic network [Global Positioning System (GPS), GPS/Global Navigation Satellite System (GLONASS) and GPS/GLONASS/Galileo] on positioning availability at three accuracy levels: 1 cm, 3 cm and 10 cm. This paper presents a mathematical model that enables the calculation of positioning availability at these levels. This model was also applied to the results of the measurement campaign performed by five GNSS geodetic receivers, made by a leading company in the field. Measurements with simultaneous position recording and accuracy assessment were taken separately on the same route for three types of receiver settings: GPS, GPS/GLONASS and GPS/GLONASS/Galileo in an urban area typical of a medium-sized city. The study has shown that applying a two-system solution (GPS/GLONASS) considerably increases the availability of high-precision coordinates compared to a single-system solution (GPS), whereas the measurements with three systems (GPS/GLONASS/Galileo) negligibly increase the availability compared to a two-system solution (GPS/GLONASS).