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The lifetime and reliability of power transformers are primarily dependent on the hot-spot temperature in the windings, as temperature is the most important factor determining the insulation degradation rate. Key to removing the heat from the transformer is the radiator which must be carefully designed to keep the temperatures within limits under all operating conditions whilst minimizing the transformer size, weight and cost. This paper compares the analytical method used to predict the radiator performance with computational fluid dynamics (CFD) models in terms of heat dissipation. It is found that the analytical method and CFD models give similar results in the air natural (AN) cooling modes, whereas the analytical method overestimates the heat dissipation in the air forced (AF) cooling modes. Moreover, the thermal conduction effect in the radiator wall is investigated under different operating conditions and for different radiator sizes using the CFD models. The simulation results indicate that the radiator wall contributes to 6%-10% of the total heat dissipation under some circumstances and therefore should not be simply ignored in radiator models.

Modelling the economics of climate change is daunting. Many existing methodologies from social and physical sciences need to be deployed, and new modelling techniques and ideas still need to be developed. Existing bread-and-butter micro- and macroeconomic tools, such as the expected utility framework, market equilibrium concepts and representative agent assumptions, are far from adequate. Four key issues—along with several others—remain inadequately addressed by economic models of climate change, namely: (1) uncertainty, (2) aggregation, heterogeneity and distributional implications (3) technological change, and most of all, (4) realistic damage functions for the economic impact of the physical consequences of climate change. This paper assesses the main shortcomings of two generations of climate-energy-economic models and proposes that a new wave of models need to be developed to tackle these four challenges. This paper then examines two potential candidate approaches—dynamic stochastic general equilibrium (DSGE) models and agent-based models (ABM). The successful use of agent-based models in other areas, such as in modelling the financial system, housing markets and technological progress suggests its potential applicability to better modelling the economics of climate change.

The stability of winter wheat-flowering-date is crucial for ensuring consistent and robust crop performance across diverse climatic conditions. However, the impact of climate change on wheat-flowering-dates remains uncertain. This study aims to elucidate the influence of climate change on wheat-flowering-dates, predict how projected future climate conditions will affect flowering date stability, and identify the most stable wheat genotypes in the study region. We applied a multi-locus genotype-based (MLG-based) model for simulating wheat-flowering-dates, which we calibrated and evaluated using observed data from the Northern China winter wheat region (NCWWR). This MLG-based model was employed to project flowering dates under different climate scenarios. The simulated flowering dates were then used to assess the stability of flowering dates under varying allelic combinations in projected climatic conditions. Our MLG-based model effectively simulated flowering dates, with a root mean square error (RMSE) of 2.3 days, explaining approximately 88.5 % of the genotypic variation in flowering dates among 100 wheat genotypes. We found that, in comparison to the baseline climate, wheat-flowering-dates are expected to shift earlier within the target sowing window by approximately 11 and 14 days by 2050 under the Representative Concentration Pathways 4.5 (RCP4.5) and RCP8.5 climate scenarios, respectively. Furthermore, our analysis revealed that wheat-flowering-date stability is likely to be further strengthened under projected climate scenarios due to early flowering trends. Ultimately, we demonstrate that the combination of Vrn and Ppd genes, rather than individual Vrn or Ppd genes, plays a critical role in wheat-flowering-date stability. Our results suggest that the combination of Ppd-D1a with winter genotypes carrying the vrn-D1 allele significantly contributes to flowering date stability under current and projected climate scenarios. These findings provide valuable insights for wheat breeders and producers under future climatic conditions.

Revolutionary catalyst protection by single layer graphene capping, tremendous catalyst lifetime longevity and activity enhancement towards oxygen reduction reaction.

National net zero emission targets could, if fully implemented, reduce best estimates of projected global average temperature increase to 2.0–2.4 °C by 2100, bringing the Paris Agreement temperature goal within reach. A total of 131 countries are discussing, have announced or have adopted net zero targets, covering 72% of global emissions. These targets could substantially lower projected warming as compared to currently implemented policies (2.9–3.2 °C) or pledges submitted to the Paris Agreement (2.4–2.9 °C). Current pledges for emissions cuts are insufficient to meet the Paris Agreement temperature goal. The wave of net zero targets being discussed and adopted could make the Paris goal possible if further countries follow suit.

Moisture availability is a strong determinant of decomposition rates in forests worldwide. Climate models suggest that many terrestrial ecosystems are at risk from future droughts, suggesting moisture limiting conditions will develop across a range of forests worldwide. The impacts of increasing drought conditions on forest carbon (C) fluxes due to shifts in organic matter decay rates may be poorly characterised due to limited experimental research. To appraise this question, we conducted a meta-analysis of forest drought experiment studies worldwide, examining spatial limits, knowledge gaps and potential biases. To identify limits to experimental knowledge, we projected the global distribution of forest drought experiments against spatially modelled estimates of (i) future precipitation change, (ii) ecosystem total above-ground C and (iii) soil C storage. Our assessment, involving 115 individual experimental study locations, found a mismatch between the distribution of forest drought experiments and regions with higher levels of future drought risk and C storage, such as Central America, Amazonia, the Atlantic Forest of Brazil, equatorial Africa and Indonesia. Decomposition rate responses in litter and soil were also relatively under-studied, with only 30 experiments specifically examining the potential experimental impacts of drought on C fluxes from soil or litter. We propose new approaches for engaging experimentally with forest drought research, utilising standardised protocols to appraise the impacts of drought on the C cycle, while targeting the most vulnerable and relevant forests.

The purpose of this study was to examine the effects of alcohol hangover on simulated highway driving performance.Driving performance of forty-two social drinkers was tested the morning following an evening of consuming on average 10.2 (SD = 4.2) alcoholic drinks (alcohol hangover) and on a control day (no alcohol consumed). Subjects performed a standardized 100-km highway driving test in the STISIM driving simulator. In addition to the standard deviation of lateral position (SDLP; i.e., the weaving of the car), lapses of attention were examined. Self-reported driving quality and driving style were scored, as well as mental effort to perform the test, sleepiness before and after driving, and hangover severity.Driving performance was significantly impaired during alcohol hangover as expressed by an SDLP increase of +1.9 cm (t (1,41) = 2.851, p = 0.007), increased number of lapses relative to the control day (7.7 versus 5.3 lapses, t (1,41) = 2.125, p = 0.019), and an increased total lapse time (182.7 versus 127.3 s, p = 0.040). During alcohol hangover, subjects reported their driving quality to be significantly poorer (t (1,41) = 4.840, p = 0.001) and less safe (t (1,41) = 5.078, p = 0.001), wise (t (1,41) = 4.061, p = 0.001), predictable (t (1,41) = 3.475, p = 0.001), and responsible (t (1,41) = 4.122, p = 0.001). Subjects further reported being significantly more tense while driving (t (1,41) = 3.280, p = 0.002), and more effort was needed to perform the driving test (t (1,41) = 2.941, p = 0.001). There was a significant interaction with total sleep time and hangover effects on SDLP and the number of lapses.In conclusion, driving is significantly impaired during alcohol hangover, as expressed in an elevated SDLP and increased number of lapses. Total sleep time has a significant impact on the magnitude of driving impairment.

Abstract This work focuses on the efforts being made by King County, Washington to respond to the challenges of global climate change, concentrating on both mitigation and adaptation. King County is a leader in the United States in the development and implementation of meaningful climate change efforts in local government. The county, in conjunction with ICLEI, recently produced a workbook on Preparing for Climate Change at the Local, Regional, and State levels. While the vast majority of local governments in the United States have only taken limited steps to respond to global warming, King County stands out as aggressively looking to move in a new direction. The King County Climate Plan is based on the conviction that climate change is both a problem and an opportunity for communities to improve environmental quality through mitigation of greenhouse gases and simultaneously build resilience to adapt to global climate change. Its exceptional combination of responsibilities in planning and opportunities makes this an invaluable experience to other local governments throughout the world. The work to be presented is a case study that examines the underlying issues and challenges faced by this jurisdiction in adopting its climate change plan; the development and adoption of the plan; issues associated with monitoring and sustaining these efforts; and the broader challenges of building more resilient and adaptive communities. The case study will focus both on procedural issues, as well as, on the types of mitigation and adaptive responses. One aspect of the paper will examine King County's efforts to link climate change efforts/policy/plans to other critical community concerns (e.g., issues of equity and race), and to the economic opportunities that have become critical motivators to successfully as moving forward the county attempts to establish itself as a global leader in meeting the challenges of global climate change.