• Energy Research
• 13. Climate action close
• 3. Good health close
• GB close
• AU close
• FI close

The COVID-19 pandemic has impacted all sectors of the tourism industry, particularly air transportation. However, air transport remains an important contributor to economic growth globally. Thus, this study examines whether air transport (a proxy for tourism) stimulates economic growth to validate the air-transportation-led growth hypothesis (ALGH) in the Australian context. To conduct the study, we analyse the asymmetric long-run and short-run impacts of the air passengers carried (a proxy for tourism) on the gross domestic product (GDP) in Australia. We use the nonlinear autoregressive distributed lag (NARDL) modelling approach on data for Australia from 1971 to 2019. We also examined the effects of selected control variables (i.e., energy consumption, financial development, socialisation, and urbanisation) on economic growth. In both the short and long run, we observed statistically significant asymmetric impacts of air transport on economic growth. The positive shocks in air transport propel the long-term growth of Australia’s economy. Additionally, according to the findings, negative shocks of air transport have a stronger detrimental impact on economic development than positive shocks.

Measurements: Rainfall - Total monthly rainfall including all precipitation (snow, rain, mist and fog) captured in a 12.7 cm rain gauge (mm per month); numbers of days with rain (0.2mm or more); the day with the maximum daily rainfall for that month. Sun shine: the total hours of sunshine recorded for the month; the day with most hours of sunshine; days when no sunshine recorded. Air temperature: the average maximum and average minimum air temperature (degrees C) for the month; the warmest day; the coldest day for the month. Frost: Numbers of air or ground frosts. The average refers to the 30-year mean 1981-2010. The summary report is derived from daily data measured at Rothamsted Research. Teses original raw data are available from the e-RA database. Daily data verification includes checks for instrument errors, missing data and outliers. These weather summaries are reported in the local Harpenden press on a monthly basis. Monthly and summaries and annual summary of rainfall, temperature, sun hours and numbers of ground frosts for 2013. Variation noted in comparison to 30-year means 1981-2010. This report consists of the monthly and annual summaries of meteorological data measured at Rothamsted Research, Harpenden, UK, from January 2013 until December 2013. Daily measurements are taken at Rothamsted Meteorological Station. These data are summarised monthly and annually as a report.

In this paper we seek to understand the impact of expanded use of soybean oil biodiesel to address biofuel mandates on global vegetable oil markets, and in particular on the demand for palm oil. An open-economy equilibrium model is derived to investigate the market effects of biodiesel expansion on related energy and vegetable oil markets. The model is calibrated to represent the recent benchmark data in calendar year 2011. The simulation estimates suggest that the expanded use of soy oil for biodiesel in the US will have considerable impacts on world vegetable oils markets. The majority of the vegetable oil replacement is likely to occur through substitution of palm oil under a wide range of plausible elasticity values on the demand for vegetable oil and the demand substitution between soy oils and palm oils.

Abstract As demands for clean and sustainable energy renew interests in nuclear power to meet future energy demands, generation IV nuclear reactors are seen as having the potential to provide the improvements required for nuclear power generation. However, for their benefits to be fully realized, it is important to explore the performance of the reactors when coupled to different configurations of closed-cycle gas turbine power conversion systems. The configurations provide variation in performance due to different working fluids over a range of operating pressures and temperatures. The objective of this paper is to undertake analyses at the design and off-design conditions in combination with a recuperated closed-cycle gas turbine and comparing the influence of carbon dioxide and nitrogen as the working fluid in the cycle. The analysis is demonstrated using an in-house tool, which was developed by the authors. The results show that the choice of working fluid controls the range of cycle operating pressures, temperatures, and overall performance of the power plant due to the thermodynamic and heat properties of the fluids. The performance results favored the nitrogen working fluid over CO2 due to the behavior CO2 below its critical conditions. The analyses intend to aid the development of cycles for generation IV nuclear power plants (NPPs) specifically gas-cooled fast reactors (GFRs) and very high-temperature reactors (VHTRs).

Abstract In case of a core melt-down accident in a light water nuclear reactor, hydrogen is produced during reactor core degradation and released into the reactor building. This subsequently creates a combustion hazard. A local ignition of the combustible mixture may generate standing flames or initially slow propagating flames. Depending on geometry, mixture composition and turbulence level, the flame can accelerate or be quenched after a certain distance. The loads generated by the combustion process (increase of the containment atmosphere pressure and temperature) may threaten the integrity of the containment building and of internal walls and equipment. Turbulent deflagration flames may generate high pressure pulses, temperature peaks, shock waves and large pressure gradients which could severely damage specific containment components, internal walls and/or safety equipment. The evaluation of such loads requires validated codes which can be used with a high level of confidence. Currently, turbulence and steam effect on flame acceleration, flame deceleration and flame quenching mechanisms are not well reproduced by combustion models usually implemented in safety tools and further model enhancement and validation are still needed. For this purpose, two hydrogen deflagration benchmark exercises have been organised in the framework of the SARNET network. The first benchmark was focused on turbulence effect on flame propagation. For this purpose, three tests performed in the ENACCEF facility were considered. They concern vertical flame propagation in an initially homogenous mixture with 13 vol.% hydrogen content and different geometrical configurations. Three blockage ratios of 0, 0.33 and 0.6 were considered to generate different levels of turbulence. The second benchmark objective was the investigation of the diluting effect on flame propagation. Thus, three tests performed in the ENACCEF facility using the same blockage ratio of 0.63 and three different initial gas compositions (with 10, 20 and 30 vol.% diluents) have been considered. Since ENACCEF runs at ambient temperature, a surrogate to steam was used consisting of a mixture of 0.6He + 0.4CO 2 on molar basis. This paper aims to present the benchmarks conclusions regarding the ability of LP and CFD combustion models to predict the effect of turbulence and diluent on flame propagation.

Whether the thermal sensitivity of an organism's traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ~0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures.

District heating is a network of pipes through which heat is delivered from a centralised source. It is expected to play an important role in the decarbonisation of the energy sector in the coming years. In district heating, heat is traditionally generated through fossil fuels, often with combined heat and power (CHP) units. However, increasingly, waste heat is being used as a low carbon alternative, either directly or, for low temperature sources, via a heat pump. The design of district heating often has competing objectives: the need for inexpensive energy and meeting low carbon targets. In addition, the planning of district heating schemes is subject to multiple sources of uncertainty such as variability in heat demand and energy prices. This paper proposes a decision support tool to analyse and compare system designs for district heating under uncertainty using stochastic ordering (dominance). Contrary to traditional uncertainty metrics that provide statistical summaries and impose total ordering, stochastic ordering is a partial ordering and operates with full probability distributions. In our analysis, we apply the orderings in the mean and dispersion to the waste heat recovery problem in Brunswick, Germany.