• Energy Research
• 13. Climate action close
• 8. Economic growth close
• 1. No poverty close
• Research Papers in Economics close

This paper proposes a polygeneration system based on a multi-input chemical looping combustion system, which generates methanol and electricity, through the use of natural gas and coal. In this system, the chemical looping hydrogen (CLH) production system and the coal-based methanol production system are integrated. A high quality fuel, natural gas, is used to improve the conversion ratio of coal. The Gibbs energy of the two kinds of fuels is fully used. Benefitting from the chemical looping process, 27% CO2 can be captured without energy penalty. With the same outputs of methanol and electricity, the energy savings ratio of the new system is about 12%. Based on the exergy analyses, it is disclosed that the integration of synthetic utilization of natural gas and coal plays a significant role in reducing the exergy destruction of the new system. The promising results obtained in this paper may lead to a clean coal technology that will utilize natural gas and coal more efficiently and economically.

Abstract This paper investigates the impact of urbanization on energy consumption by applying the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) in case of Malaysia. The study covers the time period of 1970Q1–2011Q4. The unit root test and the ARDL bounds testing approach have been applied to examine integrating properties and long run relationship in the presence of structural breaks. Our results validated the existence of cointegration and exposed that urbanization is a major contributor in energy consumption. Affluence raises energy demand. Capital stock boosts energy consumption. Trade openness leads to affluence and hence increases energy consumption. The causality analysis finds that urbanization Granger causes energy consumption. The feedback effect is found between energy consumption and affluence and, energy consumption and capital. The bidirectional causality exists between trade openness and energy consumption.

Small-scale bio-energy projects have been launched in rural areas of China and are considered as alternatives to fossil-fuel energy. However, energetic and environmental evaluation of these projects has rarely been carried out, though it is necessary for their long-term development. A village-level biomass gasification project provides an example. A hybrid life-cycle assessment (LCA) of its total nonrenewable energy (NE) cost and associated greenhouse gas (GHG) emissions is presented in this paper. The results show that the total energy cost for one joule of biomass gas output from the project is 2.93 J, of which 0.89 J is from nonrenewable energy, and the related GHG emission cost is 1.17 × 10−4 g CO2-eq over its designed life cycle of 20 years. To provide equivalent effective calorific value for cooking work, the utilization of one joule of biomass gas will lead to more life cycle NE cost by 0.07 J and more GHG emissions by 8.92 × 10−5 g CO2-eq compared to natural gas taking into consideration of the difference in combustion efficiency and calorific value. The small-scale bio-energy project has fallen into dilemma, i.e., struggling for survival, and for a more successful future development of village-level gasification projects, much effort is needed to tide over the plight of its development, such as high cost and low efficiency caused by decentralized construction, technical shortcomings and low utilization rate of by-products.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Yet fewer studies have explored the physical impacts of climate change on the power sector. The present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. The increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

This paper provides an initial analysis of the EU ETS based on the installation-level data for verified emissions and allowance allocations in the first trading year. Those data, released on May 15, 2006, and subsequent updates revealed that CO2 emissions were about 4% lower than the allocated allowances. The main objective of the paper is to shed light on the extent to which over-allocation and abatement have taken place in 2005. We propose a measure by which over-allocation can be judged and provide estimates of abatement based on emissions data and indicators of economic activity as well as trends in energy and carbon intensity. Finally, we discuss the insights and implications that emerge from this tentative assessment.

So far, various studies assessed global biomass potentials and came up with widely varying results. Existing potential estimates range from 0 EJ/a up to more than 1,550 EJ/a which corresponds to about three times the current global primary energy consumption. This paper provides an overview of the available research on bioenergy potentials and reviews the different assessments qualitative way with the objective to interpret previous research in an integrated way. In the context of this paper we understand bioenergy as energy from biomass sources including energy crops, residues, byproducts and wastes from agriculture, forestry, food production and waste management. In this review special attention was paid to the difference between residue and energy potentials, land availability estimates, and the geographical resolution of existing potential estimates. The majority of studies concentrate on energy crop potentials retrieved from surplus agricultural land and only few publications assess global potentials separated by different world regions. It results that land allocated to the exclusive production of energy crops varies from 0 to 7,000 ha, depending on land category and scenario assumptions. Only a small number of available potential assessments consider residue potentials as well as energy crop potentials from degraded land. Future energy crop potentials are assumed to vary in the mean from 200 to 600 EJ/yr. In contrast residue potentials are expected to contribute between 62 and 325 EJ/yr. The highest potentials are assigned to Asia, Africa and South America while Europe, North America and the Pacific region contribute minor parts to the global potential.