Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices

A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. An innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and ‘behaviorally-realistic’ model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. More generally, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies.     

Impact of climate change on pavement structural performance in the United States

This study uses climate projections from multiple models and for different climate regions to investigate how climate change may impact the transportation infrastructure in the United States. Climate data from both an ensemble of 19 different climate models at both RCP8.5 and RCP4.5 as well as three individual prediction models at the same Representative Concentration Pathways (RCP) levels is used. These models are integrated into the AASHTOWare Pavement ME software to predict the pavement performance. Comparisons are made between the predicted performance with respect to typical pavement distresses using both historical climate data as well as climate projection data. Though there is substantial variation for different prediction models in terms of the magnitude of the impact, the consistency in results suggest that projected climate changes are highly likely to result in greater distresses and/or earlier failure of the pavement. This finding is consistent across all the climate zones studied, but varies in magnitude of 2–9% for fatigue cracking and 9–40% for AC rutting at the end of 20 years depending on the climate region of the pavement section and prediction model used. This study also compares the impacts incorporating temperature only projections with temperature and precipitation projections. In this respect, the sections considered in this study do not show any substantial difference in the pavement performance when the precipitation data from the climate predictions are also considered in the climate inputs into AASHTOWare Pavement ME software.     

Evaluating the effects of climate change on road maintenance intervention strategies and Life-Cycle Costs

Climate change has the potential to impact long-term road pavement performance. Consequently, to maintain pavements within the same ranges of serviceability as before, current pavement maintenance strategies need to be re-assessed and, if necessary, changed. Changes in maintenance may lead to different agency costs and user costs as a consequence. This paper commences by defining an assessment procedure, showing how maintenance intervention strategies and Life-Cycle Costs (LCC) may be affected by future climate. A typical Virginia flexible pavement structure and anticipated climate change was used as an example. This example is believed to be representative for a great number of localities in the United States. A method using historical climatic data and climate change projections to predict pavement performance using Mechanistic-Empirical Pavement Design Guide (MEPDG) under current or future climate was introduced. Based on pavement performance prediction, maintenance interventions were planned and optimized. The maintenance effects of three treatments (thin overlay, thin overlay with an intermediate layer, and mill & fill) were considered. A Life-Cycle Cost analysis is reported that used binary non-linear programming to minimize the costs (either agency costs or total costs) by optimizing intervention strategies in terms of type and application time. By these means, the differences in maintenance planning and LCC under current and future climate can be derived. It was found, that for this simplified case study, pavement maintenance and LCC may be affected by climate change Optimized maintenance may improve resilience to climate change in terms of intervention strategy and LCC, compared to responsive maintenance.     

汽车空调整车环境模拟系统的仿真

建立了汽车空调整车环境模拟系统的数学模型,并在M ATLAB S/IM ULIN K软件平台上开发了汽车空调整车环境模拟系统的仿真模块库。简单介绍了所开发的仿真模块库,并用此仿真模块库对某汽车空调整车环模系统进行了仿真研究。与试验结果对比表明,所开发的仿真模块库具有很高的仿真精度。     

Scientific research about climate change mitigation in transport: A critical review

This paper seeks to develop a deeper understanding of the research on climate change mitigation in transport. We suggest that work to date has focused on the effects of improvements in transport technologies, changes in the price of transport, physical infrastructure provision, behavioural change and alternative institutional arrangements for governing transport systems. In terms of research methodologies, positivist and quantitative analysis prevails, although there are signs of experimentation with non-positivist epistemologies and participatory methods. These particular engagements with climate change mitigation reflect mutually reinforcing tendencies within and beyond the academic transport community. We first draw on a revised version of Thomas Kuhn’s philosophy of science to explore the path dependencies within transport studies, which are at least partly responsible for the predisposition towards quantitative modelling and technology, pricing and infrastructure oriented interventions in transport systems. We then employ the governmentality perspective to examine how transport academics’ engagements with climate change mitigation depend on and align with more general understandings of climate change in UK society and beyond. The analysis makes clear that ecological modernisation and neo-liberal governmentality more generally provide the context for the current focus on and belief in technological, behaviour change, and especially market-based mitigation strategies. While current research trajectories are important and insightful, we believe that a deeper engagement with theoretical insights from the social sciences will produce richer understandings of transport mitigation in transport and briefly outline some of the contributions thinking on socio-technical transitions and practice theories can make.     

Reducing the climate change impacts of aviation by restricting cruise altitudes

Two of the ways in which air travel affects climate are the emission of carbon dioxide and the creation of high-altitude contrails. One possible impact reduction strategy is to significantly reduce the formation of contrails. This could be achieved by limiting the cruise altitude of aircraft. If implemented, this could severely constrain air space capacity, especially in parts of Europe. In addition, carbon emissions would likely be higher due to less efficient aircraft operation at lower cruise altitudes. This paper describes an analysis of these trade-offs using an air space simulation model as applied to European airspace. The model simulates the flight paths and altitudes of each aircraft and is here used to calculate emissions of carbon dioxide and changes in the journey time. For a one-day Western European traffic sample, calculations suggest annual mean CO₂ emissions would increase by only 4% if cruise altitudes were restricted to prevent contrail formation. The change in journey time depended on aircraft type and route, but average changes were less than 1 min. Our analysis demonstrates that altitude restrictions on commercial aircraft could be an effective means of reducing climate change impacts, though it will be necessary to mitigate the increased controller workload conflicts that this will generate.     

秦岭终南山特长公路隧道洞口气象观测与分析

针对秦岭终南山特长公路隧道通风计算中缺少必要的洞口基本气象参数的情况,建立了洞口气象观测站,对其气象参数进行了周期一年的连续现场观测。文章根据观测结果分析了隧道洞口端各气象参数的变化规律,可为多竖井、深埋隧道通风防灾设计提供较为可靠的依据。     

南通地区气旋大风特征及预报方法研究

文章根据南通市气象台1981—2010年的气象观测资料,对南通地区大风天气的多时间尺度特征进行了分析,得出了南通地区气旋大风形势场类型,并对各型预报指标做出了总结,为今后南通地区气旋大风的预报提供参考。     

青藏铁路工程走廊多年冻土对全球气候变化的响应

针对受全球气候转暖影响青藏铁路沿线年平均气温逐年上升的环境变化,基于青藏铁路沿线不同区域内多年来的气象及地温监测资料,进行青藏铁路工程走廊气候要素演化及多年冻土对全球气候变化响应的研究。结果表明:青藏铁路工程走廊内气温基本以年均0.03℃的速度升高;年降水量大部分在250~450mm之间,且呈波动增大变化趋势;冻结指数和融化指数逐年增大,暖冬现象明显;地面温度升温速率达0.06℃·年-1,是气温升温速率的1.34倍;沿线多年冻土区2007年至2013年间天然上限抬升的仅占9%,而天然上限下降的占91%;地基多年冻土不同深度处地温均在升高,距离上限较近的地温升温速率普遍最大,多年冻土退化主要为自上而下;唐古拉山以北多年冻土退化较唐古拉山以南明显。     

Variability of snow and ice thermal, physical and optical properties pertinent to sea ice algae biomass during spring

Changes in the thermal, physical and optical properties of the snow–sea ice system and feedbacks between various temporal and spatial scales affect accumulation of microalgae at the sea ice bottom and are the focus of this research. During the spring transition period, May 4 to June 9, 2002, we closely monitored atmospheric conditions and properties of the snow–sea ice system, including thermal, physical and optical properties of the snow cover (e.g., temperature, grain size, light attenuation), ice thickness and salinity, and biomass of bottom ice algae. Results show that snowdrift size averaged 31.2 by 10.6 m with a depth range of 2 to 45 cm. Snowpacks also varied in age, distinguished by coincident peaks of snow salinity and grain size and a lower PAR extinction coefficient. Spatial variability of the snowpack was superimposed by temporal variability associated with seasonal snow–ice melt and wind redistribution of snow. Maximum biomass of ice algae was observed under intermediate snow covers. Under thin snow covers, algae biomass declined steadily coincident with seasonal warming and desalination of the ice cover. Under thick snow covers, algae biomass was negatively correlated with snow depth. These results suggest that thin snow covers were associated with a thermal effect causing sloughing of algae, whereas under deep snow, algae were still light limited and thermally insulated from the warming atmosphere. Our results highlight the importance of snow cover history on the sea ice system operating below. Furthermore, in the context of current climate change scenarios, shifts in snow depth would result in decreases of ice algae biomass.