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This paper presents the results of a survey concerning energy literacy conducted among a group of 913 students at the Cracow University of Economics in Poland—a country whose power system is still primarily based on burning coal and where the prospects of the closure of the mining sector present particularly difficult challenges. The aim of the study was to investigate specific aspects of energy literacy such as knowledge, behaviour, attitudes, and self-efficacy, and to determine what affects them using multivariate linear regression analysis. According to the findings, the primary factors determining energy literacy are gender, going away from home to study, and the experience of energy poverty. Self-efficacy, attitude, and the pro-ecological elements of both attitude and knowledge are the factors that have the most impact on students’ behaviour. The absence of a statistically significant impact of general knowledge on behaviour is a critical presumption for developing the premises of an effective pro-environment energy strategy. Based on the data, we present a number of policy proposals, including informational activity as well as ways of influencing the emotional and behavioural domains.

The threat of the negative consequences of global warming makes the discussion about the relationship between economic growth, productivity, and increasing renewable energy involvement an important topic. Hence, the aim of this study is to analyze the impact of renewable energy and energy supply on economic growth and productivity at the national level using stochastic frontier analysis and the aggregate production function framework. In doing so, we analyzed a panel of annual data from 133 countries from 2008 to 2014. We apply a generalized stochastic frontier model, which allows us to differentiate between persistent and transient inefficiency, as well as individual effects. Our results indicate a threshold level in terms of a country’s development that needs to be obtained to benefit from increasing renewable energy involvement over time. However, if this threshold level is obtained, productivity gains are evident. We also found that the role of the energy supply in aggregate production is nontrivial. That is, its inclusion changes the relationship between key input factors (capital and labor) by decreasing their overall elasticities and increasing the observed economies of scale.

Precise data processing from the Global Navigation Satellite Systems (GNSS) reference station network is mainly based on a combination of double-differenced carrier phase and code observations. This approach allows most of the measurement errors to be removed or reduced and is characterized as the most accurate method. However, creating observation differences between two receivers and two satellites increases the measurement noise of the observations by a factor of 2. As a result, it increases the impact of the incorrect definition of the noise characteristic on the results of the estimation of the unknowns in the positioning model. This is especially important in Multi-GNSS solutions, which integrate measurements from different systems, for which the stochastic parameters of observation may differ significantly. In this paper, the authors prepared a complex analysis of the noise type in double-differenced GNSS (GPS, GLONASS and Galileo) observations, both carrier phase and code ones, with a 1 s sampling interval. The Autocorrelation Function (ACF) method, the Lomb–Scargle (L-S) periodogram method, and the Allan variance (AVAR) method were used. The results that were obtained for the weekly set of measurement data showed that, depending on the system and type of observation, the noise level and its type are significantly different. Among the code measurements, the lowest noise levels were obtained for the GPS C5Q and Galileo C7Q/C8Q observations, with the standard deviations not exceeding ±10 cm, while the noisiest observations were for the GLONASS C1C and C2C signals, which had standard deviations of about ±90 cm and ±45 cm, respectively. For the carrier phase observations, each signal type was characterized by very similar noise levels of ±1.5–3.5 mm. The ACF analysis showed that 1 Hz double-differenced GNSS data can only be treated as being not correlated to time for carrier phase observations; for code observations, an irrelevant autocorrelation may be considered for measurement intervals greater than 20 s. Depending on the GNSS signals, the spectral index k varies in a range from −1.3 to −0.2 for code data and k = 0.0 in the case of phase data. Using the modified Allan deviation (MDEV) allows for specific noise types for each signal and GNSS system to be determined. All of the code observations were characterized by either flicker PM or white PM. In the case of the phase observations, they were all uniquely characterized by white PM (GPS and Galileo or by white PM and flicker PM (GLONASS).

The world has experienced increased impacts of anthropogenic global warming due to increased emissions of greenhouse gases (GHGs), which include carbon dioxide (CO2). Anthropogenic activities that contribute to CO2 emissions include deforestation, usage of fertilizers, and activities related to mining and energy production. The main objective of this paper was to assess the impacts of agriculture and energy production on CO2 emissions in Zambia. This research used econometric analysis, specifically the Autoregressive-Distributed Lag (ARDL) Bounds Test, to analyze the relationship between CO2 emissions and GDP, electricity consumption, agricultural production, and industry value added. The results showed the presence of cointegration, where the variables of CO2 emissions, GDP, electricity, and agriculture converge to a long-run equilibrium at the rate of 74%. Further, there was a short-run causality towards CO2 emissions running from agriculture and the consumption of energy as indicated by the Wald test. This is the first study of its kind that empirically shows the impact of agricultural activities and energy consumption on the Zambian environment through their contribution to CO2 emissions at a macro (country) level. This paper also presents recommendations that are pertinent to mitigate these effects. To deescalate environmental degradation, we propose increasing the number of access points for multiple renewable energy sources across the country; discouraging deforestation, the usage of conventional fertilizers, and the burning of vegetation for fertilizers; encouraging afforestation and reforestation, in addition to providing subsidies, training, and financial support to farmers and entrepreneurs who decide to use environmentally friendly agricultural methods and renewable energy. This research highlights the serious impacts of anthropogenic activities on CO2 emissions. The study was intended to assist Zambian policymakers in formulating and implementing environmentally friendly policy measures or systems that will contribute towards environmental protection commitments and sustainable economic development.

Onboard satellite clocks are the basis of Global Navigation Satellite Systems (GNSS) operation, and their revolution periods are at the level of 2 per day (about 12 h) in the case of the Medium Earth Orbit (MEO) satellites. In this work, the authors analysed the entire BeiDou Navigation Satellite System (BDS) space segment (BDS-2 and BDS-3) in terms of the occurrence of periodic, repetitive signals in the clock products, and checked if they coincide with the orbital periods or their multiples. The Lomb-Scargle (L-S) power spectrum was used as a tool to determine the periods present in the BDS clock products, allowing for analyses based on incomplete input data; in this case, the incomplete data were the phase data with jumps and outliers removed. In addition, continuous wavelet transform (CWT) was used to produce a time−frequency representation showing the more complex behaviour of the satellite clock products. As shown in the case of geostationary and geosynchronous inclined orbit satellites, the main period was 23.935 h, while for the Medium Earth Orbit it was 12.887 h, with the BDS satellite orbital period being 12 h 53 m (12.883 h). Some effects connected with reference clock swapping are also visible in the power spectrum. The conducted analyses showed that the BDS-2 satellite clocks have much higher noise than the BDS-3 satellite clocks, meaning that the number of designated periods is greater, but their reliability is significantly lower. BDS-3 satellites have only been in operation for a very short time, thus this is the first analysis to include this type of data. Moreover, such a wide and complex analysis has not been carried out to date.

Advances in remote data acquisition techniques have contributed to the flooding of society with spatial data sets and information. Widely available spatial data sets, including digital terrain models (DTMs) from aerial laser scanning (ALS) data, are finding more and more new applications. The article analyses and compares the heights of the 14 highest peaks of the Polish Carpathians derived from different data sources. Global navigation satellite system (GNSS) geodetic measurements were used as reference. The comparison primarily involves ALS data, and selected peaks’ GNSS measurements carried out with Xiaomi Mi 8 smartphones were also compared. Recorded raw smartphone GNSS measurements were used for calculations in post-processing mode. Other data sources were, among others, global and local databases and models and topographic maps (modern and old). The article presents an in-depth comparison of Polish and Slovak point clouds for two peaks. The results indicate the possible use of large-area laser scanning in determining the maximum heights of mountain peaks and the need to use geodetic GNSS measurements for selected peaks. For the Polish peak of Rysy, the incorrect classification of point clouds causes its height to be overestimated. The conclusions presented in the article can be used in the dissemination of knowledge and to improve positioning methods.

The aim of this paper is to define the factors influencing the level of energy poverty among students. The analysis of these factors is based on the results of a survey conducted among a group of 937 students at the Cracow University of Economics. The study takes into consideration the changes in the attitudes and behavior of students resulting from the introduction of distance learning during the COVID-19 pandemic. The switch to distance learning resulted in a significant increase in the number of responses related to feeling ill or sick due to inadequate temperature (from 24% before a lockdown to 32% after the introduction of a lockdown). Students experienced temporary surges in their overall living costs due to the pandemic, especially during the first wave. The respondents who experienced inappropriate temperatures (inadequate heating) due to excessive costs felt ill or became sick more often than others. The study demonstrated that those who pay more for energy (defined as a surplus payment in excess of 10%) tended to be, on average, less energy-aware than others. The following indicators of energy poverty among the students were distinguished: high living costs, small degree of influence over the choice of living quarters, as well as concerns over energy efficiency and environment. The conclusions drawn from the conducted studies may be utilized to design public policies aimed at curtailing the phenomenon of energy poverty among students. This issue is particularly prominent in large urban agglomerations where the costs of living are high and result in the feeling of pressure regarding the need to save money on thermal energy consumption.