An econometric analysis of energy input–output in Turkish agriculture

This study analyzes energy use and investigates influences of energy inputs and energy forms on output levels in Turkish agriculture during the period 1975–2000. The output level was calculated in the form of annual grain equivalent at aggregate level for 104 agricultural commodities except livestock products. Output level was specified as a function of total physical, fertilizer and seed energy, and ordinary least squares was employed to estimate equation parameters. The results show that total energy input has increased from 19.6 GJ/ha in 1975 to 45.7 GJ/ha in 2000, whereas total output energy has risen from 27.1 GJ/ha to a level of 39.1 GJ/ha. Energy efficiency indicators, input–output ratio, energy productivity and net energy have declined over the examined period. Total physical and fertilizer energy, particularly nitrogen, significantly contributed to output level with elasticities of 0.24 and 0.14, respectively. The results also revealed that non-renewable, direct and indirect energy forms had a positive impact on output level. Moreover, Turkish agriculture has experienced a substantial increase in non-renewable energy use. This inefficient energy use pattern in the Turkish agriculture can create some environmental problems such as increase in global warming, CO₂ emissions, and non-sustainability. Thus, policy makers should undertake new policy tools to ensure sustainability and efficient energy use.     

The demand for energy for irrigation in the USA

There seems to be some question concerning the relationship between irrigation and the price of energy. Did changes in the price of energy actually impact irrigation in the USA? Additionally, the substitution between alternative types of energy seems to be a possibility for irrigation. Whether in fact it occurred is another matter. In this study, an appropriate model is developed and estimated to address the issues. The specific energy types considered include motor gasoline, diesel fuel, liquefied petroleum gas, natural gas and electrical energy. The results for 1978 and for 1980 clearly indicate that energy use for irrigation is responsive to the price of energy. Additionally, some substitution between energy types took place during this period. Finally, when the question of the stability of the demand for the various energy types is addressed, the suggestion is that the demand for the energy types considered was stable for the 1978 and 1980 periods.     

Exergy analysis of the energy use in Greece

In this work, an analysis is being done on the concept of energy and exergy utilization and an application to the residential and industrial sector of Greece. The energy and exergy flows over the period from 1990 to 2004 were taken into consideration. This period was chosen based on the data reliability. The energy and exergy efficiencies are calculated for the residential and industrial sectors and compared to the findings of a previous study concerning the exergy efficiency of the Greek transport sector. The residential energy and exergy efficiencies for the year 2003 were 22.36% and 20.92%, respectively, whereas the industrial energy and exergy efficiencies for the same year were 53.72% and 51.34%, respectively. The analysis of energy and exergy utilization determines the efficiency of the economy as a whole. The results can play an important role in the establishment of efficiency standards of the energy use in various economy sectors. These standards could be utilized by energy policy makers.     

A note on energy demand estimation

This study is concerned with the assessing the impact that inaccuracy in the measurement of the dependent variable and one or more of the independent variables has on the estimate of the price elasticity of demand for diesel fuel by farmers in the United States. Two diagnostics – the regression coefficient bounds and the bias correction factor — are introduced to assess the effect that such measurement errors have on the estimated coefficients of the diesel fuel demand relationship.     

Estimation of the quality of energy sources and uses

In energy analysis and energy planning it is usual for conventional enthalpy based statistics and data to be used. This has led to difficulties, as these statistics and data do not reflect the qualities or grades of the different forms of energy. To help overcome these difficulties, a regression technique has been developed which enables all forms of energy to be converted to common quality equivalents. In particular this should improve the evaluative scope and potential of energy analysis, and in general it should aid the use of physical measurements of energy in energy planning and policy formulation procedures. Uses of the data derived from this technique, the limitations and some possible extensions of this technique are discussed.     

An analysis of future building energy use in subtropical Hong Kong

Principal component analysis of prevailing weather conditions in subtropical Hong Kong was conducted, and a new climatic index Z (as a function of the dry-bulb temperature, wet-bulb temperature and global solar radiation) determined for past (1979–2008, measurements made at local meteorological station) and future (2009–2100, predictions from general circulation models) years. Multi-year (1979–2008) building energy simulations were carried out for a generic office building. It was found that Z exhibited monthly and seasonal variations similar to the simulated cooling/heating loads and building energy use. Regression models were developed to correlate the simulated monthly building cooling loads and total energy use with the corresponding Z. Error analysis indicated that annual building energy use from the regression models were very close to the simulated values; the difference was about 1%. Difference in individual monthly cooling load and energy use, however, could be up to 4%. It was also found that both the DOE-simulated results during 1979–2008 and the regression-predicted data during 2009–2100 indicated an increasing trend in annual cooling load and energy use and a gradual reduction in the already insignificant heating requirement in cooling-dominated office buildings in subtropical climates.     

An economic analysis and energy use in stake-tomato production in Tokat province of Turkey

The aim of this study is to determine the input–output energy consumption and to make a cost analysis of intermediate type stake-tomato grown in open field in Tokat province of Turkey. The data used in the study were obtained from 98 local tomato growers using a questionnaire. The farms were chosen by random sampling method. The results showed that the amount of energy consumed in stake-tomato production was 96 957.36 MJ ha⁻¹. About 42% of this was generated by diesel oil and 38% from fertilizers and machinery. The input–output ratio was 0.80 and energy productivity was found to be 1.00 kg MJ ha⁻¹. About 76% of the total energy inputs used in stake-tomato production was non-renewable while only about 22% was renewable. These findings reveal that intensive input use in stake-tomato production, especially chemical fertilizers, gives a high tomato yield but also raises some problems like environmental pollution and global warming. Thus, new policies, emphasizing energy consumption without degradation of national resources, should be designed for such farms.     

Final energy use in IEA countries: The role of energy efficiency

Improved energy efficiency is a key policy goal of all International Energy Agency (IEA) member countries, but tracking energy efficiency gains is not straightforward. As part of its contribution to the G8 Gleneagles Plan of Action, the IEA has been developing in-depth indicators—tools that provide data and analysis of energy use and efficiency trends. This paper gives an overview of the IEA indicator methodology and presents examples of how disaggregated indicators can be used to identify the factors that drive and restrain energy demand at the end-use level. A decomposition approach is also used to separate efficiency effects from the impacts of structure and activity. The results clearly show the important role that energy efficiency has played in shaping trends in final energy use in IEA countries for more than 30 years. However, the analysis also reveals that recent gains in energy efficiency have been much lower than in earlier decades. Accelerating energy efficiency improvements is therefore a crucial challenge for IEA governments and indicators have an important role to play in helping to develop and evaluate the policies that will be required.     

Energy use,energy savings and emission analysis in the Malaysian rubber producing industries

In this paper an analysis of energy use and energy conservation in the Malaysian rubber producing industries is presented. It has been found that rubber industries consume a substantial amount of energy. Excessive use of energy is usually associated with many industrial plants worldwide, and rubber plants are no exception. This study is based on the realization that enormous potential exists for cost-effective improvements in the existing energy-using equipment. Through the method of a walkthrough energy audit, power rating, operation time of energy-consuming equipment/machineries and power factor were collected. The data were then analyzed to investigate the breakdown of end-use equipment/machineries energy use. The results of the energy audit in the Malaysian rubber and rubber producing industries showed that the electric motor accounts for a major fraction of total energy consumption followed by pumps, heaters, cooling systems and lighting. Since the electric motor takes up a substantial amount of the total energy used in rubber industries, energy-savings strategies such as the use of high efficient motors, and variable speed drive (VSD) have been used to reduce energy consumption of motors used in rubber industries. Energy-savings strategies for compressed-air systems, boilers, and chillers have also been applied to estimate energy and cost savings. It has been found that significant amount of energy and; utility bills can be saved along with the reduction of emission by applying the foretold strategies for energy using machineries in the rubber industries.     

A comparative study on energy use and cost analysis of potato production under different farming technologies in Hamadan province of Iran

The aim of this study was to determine the amount of input–output energy used in potato production and to make an economic analysis of potato production in Hamadan province, Iran. Data for the production of potatoes were collected from 100 producers by using a face to face questionnaire method. The population investigated was divided into two groups. Group I was consisted of 68 farmers (owner of machinery and high level of farming technology) and Group II of 32 farmers (non-owner of machinery and low level of farming technology). The results revealed that 153071.40 MJ ha⁻¹ energy consumed by Group I and 157151.12 MJ ha⁻¹ energy consumed by Group II. The energy ratio, energy productivity, specific energy, net energy gain and energy intensiveness were calculated. The net energy of potato production in Group I and Group II was 4110.95 MJ ha⁻¹ and −21744.67 MJ ha⁻¹, respectively. Cost analysis showed that total cost of potato production in Groups I and II were 4784.68 and 4172.64 $ ha⁻¹, respectively. The corresponding, benefit to cost ratio from potato production in the surveyed groups were 1.09 and 0.96, respectively. It was concluded that extension activities are needed to improve the efficiency of energy consumption in potato production.     

End-use energy analysis in the Malaysian industrial sector

The industrial sector is the second largest consumer of energy in Malaysia. In this energy audit, the most important parameters that have been collected are as follows: power rating and operation time of energy-consuming equipments/machineries; fossil fuel and other sources of energy use; production figure; peak and off-peak tariff usage behavior and power factor. These data were then analyzed to investigate the breakdown of end-use equipments/machineries energy use, the peak and off-peak usage behavior, power factor trend and specific energy use. The results of the energy audit showed that the highest electrical energy-using equipment was an electric motor followed by pumps and air compressors. The specific energy use has been estimated and compared with four Indonesian industries and it was found that three Malaysian industries were more efficient than the Indonesian counterpart. The study also found that about 64% electrical energy was used in peak hours by the industries and the average power factor ranged from 0.88 to 0.92. The study also estimated energy and bill savings using highly efficient electrical motors along with the payback period.     

Artificial neural network analysis of world green energy use

This paper focuses on the analysis of world green energy consumption through artificial neural networks (ANN). In addition, the consumption is also analyzed of world primary energy including fossil fuels such as coal, oil and natural gas. A feed-forward back-propagation ANN is used for training and learning processes by taking into consideration data from the literature of world energy consumption from 1965 to 2004. Also, an ANN approach for forecasting world green energy consumption to the year 2050 is presented, and the consumption equations for different energy sources are derived. The environmental aspects of green energy and fossil fuels are discussed in detail. The resulting ANN-based equation curve profiles verify that the available economic reserves of fossil fuel resources are limited, and become “depleted” in the near future. It is expected that world green energy consumption will reach almost 62.74 EJ by 2010, and be on average 32.29% of total energy use between 2005 and 2025. However, world green energy and natural gas consumption will continue increasing after 2050, while world oil and coal consumption are expected to remain relatively stable after 2025 and 2045, respectively. The ANN approach appears to be a suitable method for forecasting energy consumption data, should be utilized in efforts to model world energy consumption.     

Structural decomposition of energy use in Brazil from 1970 to 1996

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.     

An analysis of energy use and input costs for cotton production in Turkey

The aim of this study was to determine direct input energy and indirect energy in per hectare in cotton production and compare with input costs. The study also sought to analyse the effect of farm size. Data were collected from sixty five farmers using a face to face questionnaire. The sample farms were selected through a stratified random sampling technique. The results revealed that cotton production consumed a total of 49.73 GJha⁻¹ of which diesel energy consumption was 31.1% followed by fertilizer and machinery energy. Output–input energy ratio and energy productivity were 0.74 and 0.06 kg of cotton MJ⁻¹, respectively. Cost analysis showed that net return per kilogram of seed cotton was insufficient to cover costs of production in the research area. The most important cost items were labour, machinery costs, land rent and pesticide costs. Large farms were more successful in energy productivity, use efficiency and economic performance. It was concluded that energy management at farm level could be improved to give more efficient and economic use of energy.     

Inequities in domestic energy use: Some determinants

The main determinants of differences in residential energy use for space heating and space cooling arise from location, structure and design of dwelling and human behaviour. International, inter-regional and inter-household comparisons show that most available statistical data on residential energy use hide great complexity and must be disaggregated to identify real differences. Some differences are increasingly recognized as inequitous, that is, as disadvantageous to one or more groups and difficult or impossible to remove. Government energy policy mechanisms must be developed which do not increase existing inequities in the energy field, or create new ones.     

Analysis of residential energy use

The structure, inputs, validation and operation of a residential energy use model are examined with the intention of providing an analytical tool for evaluation of energy conservation option for effects on energy use and related costs.     

Biomass energy production in agriculture: A weighted goal programming analysis

Energy production from biomasses can be an important resource that, when combined with other green energies such as wind power and solar plants, can contribute to reduce dependency on fossil fuels. The aim of this study is to assess how agriculture could contribute to the production of bio-energy. A multi-period Weighted Goal Programming model (MpWGP) has been applied to identify the optimal land use combinations that simultaneously maximise farmers' income and biomass energy production under three concurrent constraints: water, labour and soil availability. Alternative scenarios are considered that take into account the effect of climate change and social change. The MpWGP model was tested with data from the Rovigo county area (Italy) over a 15-year time period.     

Conceptualizing urban household energy use: Climbing the “Energy Services Ladder”

This article begins by defining energy services and identifying how they differ according to sector, urban and rural areas, and direct and indirect uses. It then investigates household energy services divided into three classes: lower income, middle income, and upper income. It finds that the primary energy technologies involved with low-income households involve a greater number of fuels and carriers, ranging from dung and fuelwood to liquefied petroleum gas and charcoal, but a fewer number of services. Middle-income households throughout the world tend to rely on electricity and natural gas, followed by coal, liquefied petroleum gas, and kerosene. These homes utilize energy to produce a much broader range services. The upper class or rich have access to the same energy fuels, carriers, and technologies as middle-income homes and families, but consume more energy (and more high luxury items). The study highlights how focusing on energy services reorients the direction of energy policy interventions, that energy services are neither uniform nor innate, and by noting exciting areas of potential research.     

Predicting electricity energy consumption: A comparison of regression analysis,decision tree and neural networks

This study presents three modeling techniques for the prediction of electricity energy consumption. In addition to the traditional regression analysis, decision tree and neural networks are considered. Model selection is based on the square root of average squared error. In an empirical application to an electricity energy consumption study, the decision tree and neural network models appear to be viable alternatives to the stepwise regression model in understanding energy consumption patterns and predicting energy consumption levels. With the emergence of the data mining approach for predictive modeling, different types of models can be built in a unified platform: to implement various modeling techniques, assess the performance of different models and select the most appropriate model for future prediction.     

Reducing energy use in the buildings sector: measures, costs, and examples

This paper reviews the literature concerning the energy savings that can be achieved through optimized building shape and form, improved building envelopes, improved efficiencies of individual energy-using devices, alternative energy using systems in buildings, and through enlightened occupant behavior and operation of building systems. Cost information is also provided. Both new buildings and retrofits are discussed. Energy-relevant characteristics of the building envelope include window-to-wall ratios, insulation levels of the walls and roof, thermal resistance and solar heat gain coefficient of windows, degree of air tightness to prevent unwanted exchange of air between the inside and outside, and presence or absence of operable windows that connect to pathways for passive ventilation. Provision of a high-performance envelope is the single most important factor in the design of low-energy buildings, not only because it reduces the heating and cooling loads that the mechanical system must satisfy but also because it permits alternative (and low-energy) systems for meeting the reduced loads. In many cases, equipment with significantly greater efficiency than is currently used is available. However, the savings available through better and alternative energy-using systems (such as alternative heating, ventilation, cooling, and lighting systems) are generally much larger than the savings that can be achieved by using more efficient devices (such as boilers, fans, chillers, and lamps). Because improved building envelopes and improved building systems reduce the need for mechanical heating and cooling equipment, buildings with dramatically lower energy use (50–75% savings) often entail no greater construction cost than conventional design while yielding significant annual energy-cost savings.