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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.

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.

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).

Airtightness is nowadays one of the physical parameters which determine overall building energy performance. In a wide range of states, the upper limit for air change rate at a Pa (na), air permeability rate at a Pa (qa), or specific leakage rate at a Pa (wa) is determined by the formal regulations. It should be highlighted that airtightness requirements are mainly the same around the world, disregarding any site and climatic conditions. The main goal of the presented work was to reveal the effect of individual location and surrounding infiltration rate and heat demand. The analyses were done using numerical techniques and computational models of the three buildings developed and calibrated based on the blower door test results. The compared buildings characterize by a similar geometry but differ in the air change rate at 50 Pa (n50). Analyses done for different locations and levels of sheltering by surrounding elements allow the determination of the real effect of local conditions. The obtained differences in energy demand between two locations from the same climatic zone were from 70% to 90%, depending on the airtightness of the buildings. Considering different sheltered conditions, the differences for the same location can be even 200%. The obtained results allowed for the formulation of the general conclusion that building location and level of exposure could be considered in future airtightness regulations.

The topic of the article considers the functioning of the renewable energy (RE) sector in Poland. This is really important in the context of the energy transition of the national economy because it influences the creation of modern technologies and increases the competitiveness and innovation of the country. Poland is in a process of energy transition where the RE sector has been developing for two decades. The authors aimed to research the RE sector improvement possibilities in Poland, including the influence of this sector on chosen social and economic aspects. Because of this research’s aim a critical situation assessment of RE in Poland was conducted and a survey of a group of experts in this field was also involved. Legal, physical and mental determinants and their influence on RE sector were looked into. In the legal determinant context a necessity to simplify relevant legislation acts in Poland was found. Undoubtedly there is a need to improve several legal acts, including the Distance Act. In physical determinants it was found that solar, wind and biomass energy have the biggest chances for development. In the case of mental determinants the authors paid attention to the need of educating the public about using and obtaining energy. It is also important to make people aware how the RE sector influences the low emission economy positively. This will improve the creation of new jobs and reduce the emissions of harmful substances to the environment.

In this paper, petroleum product (mainly petrol and diesel) consumption in the transportation sector of China is analyzed. This was based on the Bayesian linear regression theory and Markov Chain Monte Carlo method (MCMC), establishing a demand-forecast model of petrol and diesel consumption introduced into the analytical framework with explanatory variables of urbanization level, per capita GDP, turnover of passengers (freight) in aggregate (TPA, TFA), and civilian vehicle number (CVN) and explained variables of petrol and diesel consumption. Furthermore, we forecast the future consumer demand for oil products during “The 12th Five Year Plan” (2011–2015) based on the historical data covering from 1985 to 2009, finding that urbanization is the most sensitive factor, with a strong marginal effect on petrol and diesel consumption in this sector. From the viewpoint of prediction interval value, urbanization expresses the lower limit of the predicted results, and CVN the upper limit of the predicted results. Predicted value from other independent variables is in the range of predicted values which display a validation range and reference standard being much more credible for policy makers. Finally, a comparison between the predicted results from autoregressive integrated moving average models (ARIMA) and others is made to assess our task.

The article pertains to the utilization of the application potential of MCDM/MCDA (Multi-Criteria Decision Making/Multi-Criteria Decision Analysis) methods in decision-making problems in the field of transport in light of sustainable development. The article consists of a theoretical and an empirical part. As part of the literature studies, a review was carried out on the latest applications of MCDM/MCDA methods for decision-making problems in the field of transport. In the empirical part, a multi-criteria analysis of the placement selection for a strip of expressway located in north-eastern Poland was carried out. For this purpose, a hybrid approach was used, consisting of three selected MCDM/MCDA methods: DEMATEL, REMBRANDT, and VIKOR. The ranking was compared with the results achieved in the EIA report of the investment and the results were obtained by using a different set of MCDM/MCDA methods that were proposed in the first part of the research, i.e., AHP, Fuzzy AHP, TOPSIS, and PROMETHEE. The performed multi-criteria analyses allowed for an eventual multi-dimensional evaluation of the most popular MCDM/MCDA methods currently applied in the field of transport.