Assessment Of Energy Use Research Articles

Life-Cycle Assessment of Energy Use and Greenhouse Gas Emissions of Soybean-Derived Biodiesel and Renewable Fuels

In this study, we used Argonne National Laboratory's Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model to assess the life-cycle energy and greenhouse gas (GHG) emission impacts of four soybean-derived fuels: biodiesel fuel produced via transesterification, two renewable diesel fuels (I and II) produced from different hydrogenation processes, and renewable gasoline produced from catalytic cracking. Five approaches were employed to allocate the coproducts: a displacement approach; two allocation approaches, one based on the energy value and the other based on the market value; and two hybrid approaches that integrated the displacement and allocation methods. The relative rankings of soybean-based fuels in terms of energy and environmental impacts were different under the different approaches, and the reasons were analyzed. Results from the five allocation approaches showed that although the production and combustion of soybean-based fuels might increase total energy use, they could have significant benefits in reducing fossil energy use (>52%), petroleum use (>88%), and GHG emissions (>57%) relative to petroleum fuels. This study emphasized the importance of the methods used to deal with coproduct issues and provided a comprehensive solution for conducting a life-cycle assessment of fuel pathways with multiple coproducts.

Energy use, "food miles" and greenhouse gas emissions from New Zealand dairying - how efficient are we?

Assessment of energy use and greenhouse gas emissions associated with dairy products needs to account for the whole life cycle of the products, particularly with the debate about "food miles"(the transportation of product from producer to consumer). A life cycle assessment (LCA) of an average NZ dairy farm for 2005 showed that total energy use per kg milk from the "cradle-tomilk- in-the-vat" was 45-65% of that from EU farms. The greenhouse gas (GHG) emissions or carbon footprint showed similar relative trends although differences were smaller due, at least in part, to lower methane efficiency from lower-producing NZ cows. Energy use associated with shipping dairy product (e.g. cheese) from NZ to UK is equivalent to about one-quarter of the on-farm use. Even when added together, the energy use from the NZ farm and from shipping would still be less than onfarm energy use for the EU farms. However, this is affected by intensification and the Dexcel Resource Efficient Dairying trial showed that increasing maize silage use, and nitrogen fertiliser use in particular, increased the energy use and GHG emissions per kg milk by up to 190% and 23%, respectively. Thus, the trend for intensification on NZ dairy farms means that our comparative advantage with EU farms is diminishing. A focus on improved farm system practices and integration of mitigation options is required to reverse this trend. Keywords: food miles, greenhouse gases, energy, life cycle assessment, milk, New Zealand, efficiency

Comparing High and Low Residential Density: Life-Cycle Analysis of Energy Use and Greenhouse Gas Emissions

This study provides an empirical assessment of energy use and greenhouse gas (GHG) emissions associated with high and low residential development. Three major elements of urban development are considered: construction materials for infrastructure (including residential dwellings, utilities, and roads), building operations, and transportation (private automobiles and public transit). Two case studies from the City of Toronto are analyzed. An economic input–output life-cycle assessment (EIO-LCA) model is applied to estimate the energy use and GHG emissions associated with the manufacture of construction materials for infrastructure. Operational requirements for dwellings and transportation are estimated using nationally and/or regionally averaged data. The results indicate that the most targeted measures to reduce GHG emissions in an urban development context should be aimed at transportation emissions, while the most targeted measures to reduce energy usage should focus on building operations. The results also show that low-density suburban development is more energy and GHG intensive (by a factor of 2.0–2.5) than high-density urban core development on a per capita basis. When the functional unit is changed to a per unit of living space basis the factor decreases to 1.0–1.5, illustrating that the choice of functional unit is highly relevant to a full understanding of urban density effects.

Energy Use and Output Assessment of Food‐Forage Production Systems

AbstractAn assessment of the energy requirements of different intensive forage production systems was carried out at the Indian Grassland Fodder, and Agroforestry Research Institute, Jhansi. This included assessment of energy use and output for five intensive crop production systems: (1) sorghum (single‐cut)–berseem, (2) cowpea–sorghum (single‐cut)–berseem + mustard–maize + cowpea, (3) sorghum (multi‐cut)–berseem + oats, (4) guar–oats–maize and (5) sorghum (single‐cut)–wheat–fallow. In all the systems, the Napier bajra hybrid (IGFRI‐3) was transplanted in regular plots of 50 m × 13 m. Results revealed that the total annual energy use was highest for sorghum (multi‐cut)–berseem + oats (36 606 MJ ha−1), followed by sorghum (single‐cut)–berseem + mustard, sorghum (single‐cut)–berseem–cowpea, guar–oats–maize and sorghum (single‐cut)–wheat–fallow (for which values were 31 086, 30 449, 29 867 and 25 956 MJ energy ha−1, respectively). The high value found for sorghum (multi‐cut)–berseem + oats might be attributable to the multi‐cuts in this system. Energy use by fertilizers represented the major part of the total energy use, amounting to 28–38 % in all treatments, followed by energy used in electricity, machinery, seeds, human labour and farmyard manure (FYM), in case of all with slight increase in input. In sorghum–wheat, energy use by seeds occupied the second position, followed by energy used in electricity, human labour, FYM and machinery/diesel. Pesticides contributed the least energy utilization in all the treatments. Herbicides were used for the control of weeds. Among the five forage production systems, sorghum (single‐cut)–berseem + mustard–maize + cowpea was found to be the most energy efficient, followed by sorghum (multi‐cut)–berseem + oats–sorghum (multi‐cut), sorghum (single‐cut)–berseem–cowpea, guar–oats–maize and sorghum (single‐cut)–wheat–fallow. Sorghum (single‐cut)–berseem + mustard–maize + cowpea increased the fertility of the soil, resulting in a higher percentage of organic carbon, higher availability of nitrogen and optimal balancing of the C:N ratio in the upper layers of the soil. These intensive crop production systems also maintain the optimum microbial population in the crop root zone. The benefit–cost ratio (B:C ratio) for the most energy‐efficient forage production system was 1.37 : 1. However, the highest B:C ratio was found in the sorghum–wheat rotation (1: 1.57).

Assessment of energy use in arable farming systems by means of an agro-ecological indicator: the energy indicator

Efficient energy use by the agriculture sector is one of the conditions for sustainable agriculture because it allows financial savings, fossil resources preservation and air pollution decrease. We propose an Energy indicator ( I En) to evaluate environmental impacts due to energy consumption of arable farming systems to help farmers to manage their energy inputs at the field level according to the guidelines of integrated agriculture. I En is based on the energetic analysis of four types of energy: two for indirect energy (pesticides and fertilisers) and two for direct energy (machinery and irrigation systems). In a second step, the assessed values of energy consumption are converted by means of an abacus into a mark between 0 and 10. I En needs only data that are available on farms or easily assessed, and will be implemented with a set of seven other agro-ecological indicators to assess environmental sustainability of farms.

Weighted Digraph Models for the Assessment of Energy Use and Air Pollution in Transportation Systems

This paper describes extensions, to weighted and double-weighted digraphs, of the author's earlier work on building and analyzing energy-demand signed digraphs. Several weighted and double-weighted digraphs are built to provide a test of the construction methodology, to provide a test of the methods of analysis of such digraphs, and to illustrate the type of analysis one can make using such digraphs as models of complex systems. The digraphs are constructed within the context of the transportation system of a hypothetical metropolitan area, similar to the County of San Diego, California. The digraphs are used to compare fuel consumption and air pollution under two scenarios: the nominal case, where clean air standards are met by some retrofitting of cars with smog control devices; and the bus case, where cars are banned and an expensive wide-ranging bus system is introduced. It is concluded that weighted and double-weighted digraphs can be constructed relatively inexpensively and that at least weighted, and probably double-weighted, digraphs can be used at an early stage of a policy-making task to set directions for further research.