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Studien syftar till att undersöka klimatmedvetenhet i relation till matvanor hos en grupp unga svenska vuxna, och att undersöka dess samband med fysisk aktivitetsnivå och kön. Följande forskningsfrågor ställdes: Hur kan sambandet mellan matvanor, aktivitetsnivåer och kön förstås i termer av energiintag, koldioxidavtryck och proteinkällor? Hur påverkar olika aspekter av matvanor koldioxidavtrycket? Hur beaktas hållbarhet inom ramen för matvanor? Denna studie använde en mixed-method-ansats som kombinerade intervjuer och data från projektet Measuring Energy Expenditure and Dietary Intake at Different Activity Levels (MEDAL). En sju dagars matregistrering gav detaljerade insikter i deltagarnas matintag med fokus på proteinkällor och koldioxidavtryck (CO2e). Deltagare i åldrarna 18-40 rekryterades från Göteborgs universitet och lokala idrottsklubbar mellan oktober 2020 och april 2021. De delades in i två grupper baserat på deras fysiska aktivitetsnivåer, enligt WHO riktlinjer. Datainsamlingen inkluderade semistrukturerade intervjuer och en sju dagars matregistrering med hjälp av onlineverktyget Nutrition Data. Energiförbrukning i vila mättes med indirekt kalorimetri. Intervjuerna undersökte matköpsvanor, kostpreferenser och klimatpåverkan utan att direkt informera deltagarna om klimatfokuset för att undvika bias. Kvantitativa data analyserades med statistiska tester, medan kvalitativa insikter triangulerades med kostregistreringarna för att bedöma eventuellt klimatmedvetna och hållbara matvanor. Analysen guidades av social praktik teori, med fokus på samspelet mellan deltagarnas attityder och beteenden. Statistisk analys genomfördes med SPSS, och signifikanta resultat bestämdes med ett p-värde på 0,05 eller lägre. This study employed a mixed-method approach combining interviews and data from the Measuring Energy Expenditure and Dietary Intake at Different Activity Levels (MEDAL) project. A seven-day food record provided detailed insights into participants' food intake, focusing on protein sources and carbon footprint (CO2e). Participants, aged 18-40, were recruited from Gothenburg University and local sports clubs between October 2020 and April 2021. They were divided into two groups based on their physical activity levels, following WHO guidelines. Data collection included semi-structured interviews and a seven-day food record using the Nutrition Data online tool. Resting energy expenditure was measured using indirect calorimetry. The interviews explored food shopping habits, dietary preferences, and climate impact considerations without directly informing participants of the climate focus to avoid bias. Quantitative data were analyzed with statistical tests, while qualitative insights were triangulated with food records to assess climate-conscious and sustainable food consumption practices. The analysis was guided by social practice theory, focusing on the interplay between participants' attitudes and behaviors. Statistical analysis was conducted using SPSS, and significant findings were determined with a p-value of 0.05 or lower.

The Environmental Displacement Dataset (EnDis) quantifies human movement in response to sudden-onset natural hazards, including floods, storms, wildfires, landslides, earthquakes, and volcanic activity.

The most widely used process for hydrogen production is steam methane reforming. It can be carried out using a membrane reactor in which simultaneous hydrogen production and purification occur. Mathematical modeling of these reactors plays a key role in the selection of the design and operating parameters that yield high performance for the reactor. This review study discusses, synthesizes, and compares different mathematical modeling studies on the packed bed membrane reactors for hydrogen production from methane found in the literature. Different approaches used in these modeling studies for the hydrogen permeation steps, reaction kinetic expressions, phases involved (pseudo-homogeneous and heterogeneous), and spatial dimensions (one, two, and three dimensional) are given.

Climate-controlled changes in eustatic sea level (ESL) are linked to transfers of water between ocean and land, thus offering a rare insight into the past hydrological cycle. In this study, we examine the timing and phase of Milankovitch-scale ESL cycles in the peak Cretaceous greenhouse, the early Turonian (-93-94 million years, Myr, ago). A high-resolution astronomical framework established for the Bohemian Cretaceous Basin (central Europe) suggests a -400-kyr pace and a distinct asymmetry of interpreted ESL cycles. The rising limbs of ESL change constitute only 20-30 % of the cycle, and are encased entirely within the falling phase of the 405-kyr eccentricity. The intervening ESL falls (<= 6 m in magnitude) are more protracted, starting within 70 kyr prior to the eccentricity minima and culminating -60 kyr after the 405-kyr eccentricity maxima. Despite similarities to the sawtooth shape of -100-kyr glacioeustatic oscillations of the Late Pleistocene, the time scales and phasing are unparalleled in the Pleistocene icehouse. A similar, 405-kyr pace is found in ice-volume variations of the early Miocene, but the timing of glacioeustatic change relative to eccentricity forcing is incompatible with the phase of greenhouse sea-level oscillations. The phasing points to major differences in the geographic location and insolation sensitivity of the key hydrological reservoirs under icehouse and greenhouse regimes. The inferred structure of greenhouse eustasy points to low- or middle-latitude water storage, likely aquifers, that charge (expand) with rising seasonality variations and discharge (contract) with declining seasonality amplitudes on the 405-kyr scale. The net volume of water transferred on these time scales is within 2.2 x 106 km3, equivalent to <= 10 % of the present-day storage in the uppermost 2 km of continental crust. Potential additive interference with steric eustasy, proportionally relevant during greenhouse regimes, could reduce the volumes required for continental storage.

Abstract In the current transition to a smarter and more efficient transportation system, battery electric vehicle mileage and the time required for charging are still two main constraints that need to be overcome to enable a larger penetration of electric vehicles. Moreover, the few charging stations available are a consequence of the “supply and demand” problem. Consequently, wireless dynamic recharging can be a complementary solution to address the problems of light-duty electric mobility and an added-value towards autonomous vehicles. Consequently, this paper presents an innovative approach based on real world mobility patterns collected for a sample in the city of Lisbon, Portugal, to assess users’ electric vehicle feasibility by assessing different recharging scenarios, comparing stationary and dynamic recharging scenarios. The results indicate that at least 15 % more drivers would be eligible to own an electric vehicle if wireless charging was available. Moreover, wireless charging reduces the range of battery used, with stationary charging requiring circa 3.2 times more battery range. The developed approach confirms that wireless dynamic recharging can significantly change the framework of current electric mobility limitations, reducing range anxiety issues, contributing to redesign electric vehicle battery capacity and overcome barriers in stationary charging deployment and availability.

The paper presents a computer simulation of the operation of three independent electric drives with a periodic load, connected to a common power supply network. Two cases are considered - operation of electric drives in one phase and in different phases. An analysis of their impact on the electrical supply network is carried out, the results are compared with the permissible Russian standards. An analytical optimization method based on the analysis of power graphs of electric drives with periodic load was considered. The article contains an overview of possible methods for regulating the working phase of the mechanism.

Growing interest of the European Union to introduce new emission regulations seeking to lower the particle cut-off size down to the current limit set at 23 nm, has made crucial to achieve an extensive comprehension on their nature. In this regard, it is necessary to deepen their knowledge under different engine technologies, operating conditions, fuel properties and after-treatment devices and how their measure is affected by the sampling and dilution procedure. This paper provides a study on the sub-23 nm particles emitted from a small direct/port fuel injection, spark ignition engine fueled with gasoline, ethanol and a 30% v/v ethanol/gasoline blend, at different operating conditions. Particles were measured both upstream and downstream of a three-way catalyst. The conditions of the sampling were changed in order to investigate the volatile organic fraction. For this purpose, the exhaust gas sample was diluted through a Particulate Measurement Programme compliant system. The temperature of the first dilution stage and of evaporation chamber were changed to discriminate the volatile compounds by enhancing the condensation and the nucleation processes. An engine Exhaust Particle Sizer was used for the sizing and the counting of the particles in the range 5.6-560 nm. The results show a strong dependence of the sub-23 nm particle emissions from the engine operating condition and the fuel type. A moderate impact of the three-way catalyst was instead observed. Moreover, a significant effect of the dilution parameters in the sampling system was noted pointing out the importance to define an appropriate protocol for the measurement of the sub-23 nm particles.

Worldwide, the energy consumption of refrigeration systems increased by 50% in the last 20 years. Currently, active refrigeration systems are often used to maintain cold chains in industry. However, there are remarkable drawbacks in the operation of active systems such as susceptibility to blackouts in the power supply and vibrations during their operation. Therefore, to overcome the aforementioned problems, passive cold chain transport using latent thermal energy storage systems arose as a potential solution. However, these systems require long charging times due to the low thermal conductivity of most phase change materials. In that sense, this paper presents a novel design of a cold storage battery with metal foam enhanced phase change material. The peak efflux of energy and solidification time of the battery is correlated as a function of the inlet temperature and mass flow rate of the heat transfer fluid with a root mean square deviation of 11.4%. The solidification time prediction allows determining the geometry which results in the maximum efflux of energy density for a given energy density. Moreover, the cold battery is placed in an insulated container to analyse its performance during transport. Results show that the tested refrigeration battery can act as a standalone refrigeration system during 15 h. However, improvements in the design of the insulated container are suggested to increase the performance of the system along the discharging cycle.

A correlation analysis based on Markowitz Portfolio Theory and data from meteorological station are used to develop a decision-making tool for the optimal spatial installation of renewable energy sources from Wind turbines and PV panels. A case study involving power generation plants and weather stations in the region of Tuscany in Italy is developed. The results show that temporal correlations of solar and wind generation profiles are characterized by correlation and anticorrelation. This feature is used for supporting deci­sion-making on investments in renewable energy at the territorial level.