• Energy Research
• 8. Economic growth close
• GB close
• MY close
• Applied Energy close

This paper examines the sources of changes in energy use of the Brazilian economy of industries and households from 1970 to 1996, using structural decomposition analysis based on the logarithmic mean divisia index technique. Energy use can be decomposed into eight factors that explain changes in overall energy use over the entire time period, and within five sub-periods. The growth of energy use between 1970 and 1996 was mainly influenced by changes in affluence, population and intersectoral dependencies, while changes in direct energy intensity and per capita residential energy use had a retarding impact on energy use. The novel contributions of the paper are the alignment of a previously disparate data set, the use of supply-use tables for SDA, and the application of such an SDA to a developing country. Both contributions involve solving a range of methodological issues pertaining to handling of large data sets.

Integrated analysis and optimization of material and energy flows in the iron and steel industry have drawn considerable interest from steelmakers, energy engineers, policymakers, financial firms, and academic researchers. Numerous publications in this area have identified their great potential to bring significant benefits and innovation. Although much technical work has been done to analyze and optimize material and energy flows, there is a lack of overview of material and energy flows of the iron and steel industry. To fill this gap, this work first provides an overview of different steel production routes. Next, the modelling, scheduling and interrelation regarding material and energy flows in the iron and steel industry are presented by thoroughly reviewing the existing literature. This study selects eighty publications on the material and energy flows of steelworks, from which a map of the potential of integrating material and energy flows for iron and steel sites is constructed. The paper discusses the challenges to be overcome and the future directions of material and energy flow research in the iron and steel industry, including the fundamental understandings of flow mechanisms, the dynamic material and energy flow scheduling and optimization, the synergy between material and energy flows, flexible production processes and flexible energy systems, smart steel manufacturing and smart energy systems, and revolutionary steelmaking routes and technologies.

Abstract Employees constitute a large target group for energy conservation. Companies that want to reduce their energy consumption should promote their employees’ participation. For successful energy saving in companies, employees should save energy on a continued basis, and develop the habit of energy saving. Unfortunately, success in having employees continue to save energy in organization is difficult. Motivated by such concern, taking office workers as example, this study develops a model to explain employee electricity saving habit in organization. Determining factors are identified based on social exchange theory, norm activation model and literature on threat and harm. Data were collected through a survey of 211 office workers from 10 organizations in Northern China. Partial Least Square (PLS) path modeling was used to analyze the collected data. The results show that enjoyment, personal norm, image and perceived harm significantly influence employee energy saving habit in organization. While anticipated extrinsic benefit and perceived threat do not have significant impact. This paper contributes to the energy saving literature by studying employee energy saving habit in organization.

AbstractClean burning products, for example cooking stoves, can reduce household air pollution (HAP), which prematurely kills 3.5 million people each year. By careful selection of components into a product package with micro-finance used for the capital payment, barriers to large-scale uptake of products that remove HAP are reduced. Such products reduce smoke from cooking and the lighting from electricity produced, eliminates smoke from kerosene lamps. A bottom-up financial model, that is cognisant of end user social needs, has been developed to compare different products for use in rural areas of developing countries. The model is freely available for use by researchers and has the ability to assist in the analysis of changing assumptions. Business views of an individual villager, the village itself and a country view are presented. The model shows that affordability (defined as the effect on household expenses as a result of a product purchase) and recognition of end-user social needs are as important as product cost. The effects of large-scale deployment (greater that 10 million per year) are described together with level of subsidy required by the poorest people. With the assumptions given, the model shows that pico-hydro is the most cost effective, but not generally available, one thermo-acoustic technology option does not require subsidy, but it is only at technology readiness level 2 (NASA definition) therefore costs are predicted and very large investment in manufacturing capability is needed to meet the cost target. Thermo-electric is currently the only technology that can be used worldwide every day of the year and is available without research. However, it is not yet self-financing and therefore requires subsidy or diversion of more household income to be affordable. A combination of photovoltaic and clean cookstove may be suitable in areas where sufficient solar radiation is available on most days. Affordability is shown to be highly dependent on the income that can be derived from carbon credits.

Demand elasticity for petrol or diesel is an important policy parameter, both from energy security and global warming perspective. Despite an abundance of literature on petrol demand, there are few studies on diesel demand, and even fewer on demand by different vehicle types. This paper aims to model diesel demand for different freight duty vehicle types (e.g. heavy vs. light goods vehicles and rigid vs. articulated trucks) in the UK. We argue that the switch to diesel from petrol engines in the light vehicles sectors could have biased earlier petrol or diesel demand elasticities in Europe, and show that it was indeed the case for the light goods vehicle sector. Results show that both light and heavy goods vehicles have similar income elasticities, although within the heavy duty sector, articulated trucks are more elastic than rigid trucks. Overall, heavy goods vehicles were responsive to fuel prices, but light goods vehicles were not. Within the heavy duty sector, rigid trucks showed statistically significant price elasticity, but articulated trucks did not respond to changes in fuel prices. Our results show that price-based policies to curb fuel consumption from the light or heavy goods vehicles are unlikely to be effective.

Abstract This paper presents a novel approach to demand forecasting for both crude oil and natural gas: it can be applied with confidence for any country that is politically and economically stable. However, because of these uncertainties and social factors, it is often difficult to formulate a wise policy concerning long-term energy requirements. None the less, there is a need for each country to formulate a sustainable energy strategy. Thus it is desirable to be able to predict accurately future demand requirements for crude oil and natural gas, and so a mathematical model has been developed that can be used with readily-available standard data: it is referred to as the ‘modified logit-function demand model’. It is based on saturation curve extrapolations for the appropriate energy intensity (i.e. fuel consumption/GDP), population and GDP/capita. When new input data become available, revised and hence improved projected-demand estimates can be derived readily.

Abstract Although aspects of long-term planning are commonly taken into account in current analyses of bioenergy policy scenarios, representations of the bioenergy supply chain are often spatially aggregated. Multiple questions such as where, when, and how bioenergy is deployed have thus not been sufficiently addressed within a single modeling framework. Moreover, techno-economic models that can capture the dependencies of bioenergy supply chain variables among end-use sectors still need to be explored. The present research connects these gaps by presenting the development of a spatio-temporal techno-economic optimization model for cross-sectoral bioenergy policy evaluations under high spatial resolution and long-term temporal resolution. The research recognizes not only the need for energy decarbonization, but also the importance of improving resource efficiency in the palm oil industry, in this case, Malaysia’s palm oil bioenergy industry. The findings highlight the need for multi-sectoral collaboration between the energy sectors to deliver cost-optimal energy decarbonization at the national scale. This is represented by the substitution of up to 30%, 27%, and 12% of the energy demands in the power, heat, and transport sectors with bioenergy, respectively. The conflict between policy targets was also highlighted, namely, that new policies prioritizing bioenergy in the power and transport sectors reduce CO2 more effectively than policies targeting CO2 reduction alone, however, requiring up to 37% more cost in meeting the CO2 reduction commitment. The findings also outline the requirement of co-locating bioenergy production facilities with the existing facilities (e.g., agricultural mills, coal plants) and extending the existing infrastructure network to deliver the bioenergy capacities needed to meet the policy targets.

Abstract Environmental policies often underperform due to so-called rebound effects, namely behavioural and systemic responses to technical change leading to additional consumption and environmental damage. While evidence of rebound is abundant, studies generally focus on technical changes that are neither associated with specific technologies nor their production costs, making it difficult to connect these changes with the policies governing them. To overcome this limitation, this study proposes to combine a technology-rich model based on life cycle assessment and a behaviour-optimising model for the global economy based on computable general equilibrium modelling. This approach allows to quantify policy-induced economy-wide rebound effects for four relevant environmental impacts: climate change, acidification, photochemical ozone formation, and particulate matter. We apply this approach to evaluate the effectiveness of the United Kingdom’s subsidy on electric cars. The results show notable economy-wide rebound effects associated with this subsidy: over or close to 100% (no environmental benefits) for acidification and particulate matter impacts, and a lower, yet notable, magnitude for climate change (~20–50%) and photochemical ozone formation (~30–80%) impacts. The results also show the important role of macro-economic effects from price changes, particularly how the shift from petrol to electricity triggered additional demand for cheaper petrol.

Productivity in Nigeria is decreasing: this has adversely affected the average standard-of-living of the population and led to economic hardship. HIV/AIDS, hunger, disease and wars have lowered African productivity and the effectivenesses of public utilities have declined, while unemployment and crime are on the increase. A computer program, which considers the combined concept of partial productivity, total productivity measurement and reliability in order to analyse the effectiveness of a firm, society or nation has been developed. Its predictions have been tested with data from a Nigerian petroleum-product marketing company, namely Rock Oil and Gas Ltd., Aba, Abia State: the management of this business is representative of those of many Nigerian firms. The developed software (see Appendix) can help in identifying the causes of productivity problems, which can so adversely affect the performance of any organisation.