• Energy Research
• 11. Sustainability close
• CN close
• NL close
• DE close
• Tsinghua University close

Abstract The central role of occupants for achieving energy savings in residential buildings is increasingly recognised. Simulation programmes able to take into account occupant behaviour are considered to be powerful tools for bridging the gap between the predicted and the actual energy consumption for new buildings. Nevertheless, the majority of residential buildings that will constitute the housing stock in 2050 have already been built today, therefore occupant behaviour and building simulation tools need to be fully exploited for supporting the renovation of existing housing stock. The aim of this paper is to explore the role of occupant behaviour modelling in supporting decision-makers dealing with the design of renovation strategies for residential buildings. An Italian multi-family public housing building is assumed as case study to estimate the influence of three dimensions linked with occupant behaviour – management of the thermostat, management of the heating system, variation of building characteristics – on energy heating consumption. The results show that, while the occupant behaviour influences the heating loads up to 1/3 in case of high level of building retrofit, the less the building is renovated, the higher is the behavioural impact in absolute terms of energy reduction. Therefore, in order to be effective, renovation strategies are required to design appropriate informative instruments at an early stage to support behaviour changes towards responsible energy consumption.

Abstract Natural gas vehicles offer the benefits of reducing oil use, CO2 emissions and air pollutants. Promoting the use of natural gas vehicles is considered as one of the most important strategies towards sustainable transportation. China made remarkable progress in promoting natural gas vehicles over recent years, and its 4.6 million natural gas vehicles in 2014 represented the world׳s largest natural gas vehicle fleet. In this paper, the development of natural gas vehicles in China is reviewed based on a triple-perspective (Fuel-Vehicle-Infrastructure) technical–economical framework. The review indicates that (a) pricing of vehicle-use Compressed Natural Gas (CNG) and Liquefied Natural Gas (LNG) is essential in determining natural gas vehicle development. A pricing principle similar to the fixed CNG/gasoline price ratio (0.75:1) should be applied to LNG/diesel price ratio; (b) for CNG passenger vehicles, the modified CNG vehicles, with ¥3000–5000 additional cost, is more attractive to consumers than originally manufactured CNG vehicles, with about ¥10,000 additional cost. Vehicle retrofit should be permitted by the government with the precondition that retrofit standards are strictly enforced; (c) for CNG/LNG transit buses, the deployment is strongly affected by local government׳s preference. In regions with sufficient natural gas supply, the government should prioritize the deployment of CNG/LNG transit buses rather than other technologies; (d) for LNG commercial vehicles, with ¥60,000–80,000 higher cost than their counterpart diesel vehicles, financial incentive is critical for their development. China׳s current vehicle subsidy scheme should be extended to cover LNG commercial vehicles; (e) regarding refueling infrastructures, interference with urban land-use planning and long-time administrative approval are the major barriers. Local governments should launch dedicated plans and strategies to support the further deployment of CNG/LNG refueling infrastructures.

Abstract Rapid economic growth and accelerating urbanization in the past three decades have accelerated the exhaustion of China’s mineral resources. China is the world’s largest consumer and importer of nickel resources; therefore, a growing domestic demand will increase China’s import dependence and in turn make it potentially vulnerable to supply shortages. One hundred years from 1950 to 2050 were examined for China’s nickel utilization. Identified domestic nickel resources can only sustain China’s industries until 2017, but nickel will reach peak utilization around the year of 2020–2022. Given the 5% annual increase in applications and the growing importation of minerals in China, the carrying duration of nickel resources until 2020 will require a nickel-recycling rate of more than 90%. To sustain China’s nickel utilization, future strategies should foster three solutions: maintaining a high level of imports, adjusting the landscape of nickel applications, and shifting from virgin mining of geological minerals to urban mining of anthropogenic resources.

This is the companion paper of part I of DeST overview. DeST was developed as a building simulation tool with the aim of benefiting both design of and research on building energy efficiency. During its development, DeST has been applied to many projects, development of building regulations, and research. This paper gives examples of several areas in which DeST has been applied, including building design consultation, building commissioning, building energy conservation assessment, a building energy labeling system, and scientific research. Examples from a demonstration building are presented to demonstrate the entire process of aiding design with DeST. Additional projects and regulations are also mentioned to introduce other applications of DeST.

Building occupancy is an important basic factor in building energy simulation but it is hard to represent due to its temporal and spatial stochastic nature. This paper presents a novel approach for building occupancy simulation based on the Markov chain. In this study, occupancy is handled as the straightforward result of occupant movement processes which occur among the spaces inside and outside a building. By using the Markov chain method to simulate this stochastic movement process, the model can generate the location for each occupant and the zone-level occupancy for the whole building. There is no explicit or implicit constraint to the number of occupants and the number of zones in the model while maintaining a simple and clear set of input parameters. From the case study of an office building, it can be seen that the model can produce realistic occupancy variations in the office building for a typical workday with key statistical properties of occupancy such as the time of morning arrival and night departure, lunch time, periods of intermediate walking-around, etc. Due to simplicity, accuracy and unrestraint, this model is sufficient and practical to simulate occupancy for building energy simulations and stochastic analysis of building heating, ventilation, and air conditioning (HVAC) systems.

Indoor humidity directly impacts the health of indoor populations. In arid and semi-arid cities, the buildings indoor humidity is typically higher than outdoors, and the presence of water vapor results from water dissipation inside the buildings. Few studies have explored indoor humidity features and vapor distribution or evaluated water dissipation inside buildings. This study examined temperature and relative humidity (RH) changes in typical residential and office buildings. The results indicate a relatively stable temperature with vary range of ±1°C and a fluctuation RH trend which is similarly to that of water use. We proposed the concept of building water dissipation to describe the transformation of liquid water into gaseous water during water consumption and to develop a building water dissipation model that involves two main parameters: indoor population and total floor area. The simulated values were verified by measuring water consumption and water drainage, and the resulting simulation errors were lower for residential than for office buildings. The results indicate that bathroom vapor accounts for 70% of water dissipation in residential buildings. We conclude that indoor humidity was largely a result of water dissipation indoors, and building water dissipation should be considered in urban hydrological cycles.

Net anthropogenic emissions of carbon dioxide (CO2) must approach zero by mid-century (2050) in order to stabilize the global mean temperature at the level targeted by international efforts1-5. Yet continued expansion of fossil-fuel-burning energy infrastructure implies already 'committed' future CO2 emissions6-13. Here we use detailed datasets of existing fossil-fuel energy infrastructure in 2018 to estimate regional and sectoral patterns of committed CO2 emissions, the sensitivity of such emissions to assumed operating lifetimes and schedules, and the economic value of the associated infrastructure. We estimate that, if operated as historically, existing infrastructure will cumulatively emit about 658 gigatonnes of CO2 (with a range of 226 to 1,479 gigatonnes CO2, depending on the lifetimes and utilization rates assumed). More than half of these emissions are predicted to come from the electricity sector; infrastructure in China, the USA and the 28 member states of the European Union represents approximately 41 per cent, 9 per cent and 7 per cent of the total, respectively. If built, proposed power plants (planned, permitted or under construction) would emit roughly an extra 188 (range 37-427) gigatonnes CO2. Committed emissions from existing and proposed energy infrastructure (about 846 gigatonnes CO2) thus represent more than the entire carbon budget that remains if mean warming is to be limited to 1.5 degrees Celsius (°C) with a probability of 66 to 50 per cent (420-580 gigatonnes CO2)5, and perhaps two-thirds of the remaining carbon budget if mean warming is to be limited to less than 2 °C (1,170-1,500 gigatonnes CO2)5. The remaining carbon budget estimates are varied and nuanced14,15, and depend on the climate target and the availability of large-scale negative emissions16. Nevertheless, our estimates suggest that little or no new CO2-emitting infrastructure can be commissioned, and that existing infrastructure may need to be retired early (or be retrofitted with carbon capture and storage technology) in order to meet the Paris Agreement climate goals17. Given the asset value per tonne of committed emissions, we suggest that the most cost-effective premature infrastructure retirements will be in the electricity and industry sectors, if non-emitting alternatives are available and affordable4,18.

This research examines the role of poverty and logistical operations under the circumstance of environmental deterioration with panel data of ASEAN states from 2007 to 2017. The system-generalized method of moments (GMM) was adopted due to the presence of endogeneity. The results indicate that poverty and logistical operations have significant and positive relationship with greater environmental degradation. Because poor people are not skilled, they have to consume natural resources in original and unsustainable way for their survival and profits, which results in greater level of deforestation. On another hand, lacking fuel-efficient/green vehicles and green practices in logistical operations of ASEAN countries, logistics activities mainly depend on fossil fuel consumption, which generates greater carbon emission, methane, and greenhouse emissions that can directly damage the environment and become a primary source of climate change. Therefore, reduction in environmental degradation can be achieved through reduction in poverty and encouraging renewable energy and green practices in logistical operations. In addition, this study also provides detailed policy implications to regulatory bodies and corporate sector in order to improve environmental sustainability through adoption of green practices and reduction in poverty.

Energy storage has great potential in grid congestion relief. By making large-scale energy storage portable through trucking, its capability to address grid congestion can be greatly enhanced. This paper explores a business model of large-scale portable energy storage for spatiotemporal arbitrage over nodes with congestion. We propose a spatiotemporal arbitrage model to determine the optimal operation and transportation schedules of portable storage. To validate the business model, we simulate the schedules of a Tesla Semi full of Tesla Powerpack doing arbitrage over two nodes in California with local transmission congestion. The results indicate that the contributions of portable storage to congestion relief are much greater than that of stationary storage, and that trucking storage can bring net profit in energy arbitrage applications. Submitted to IEEE PES GM 2019; 5 pages,4 figures