Uncertainty Analysis in Biofuel Systems

This article evaluates the implications of uncertainty in the life cycle (LC) energy efficiency and greenhouse gas (GHG) emissions of rapeseed oil (RO) as an energy carrier displacing fossil diesel (FD). Uncertainties addressed include parameter uncertainty as well as scenario uncertainty concerning how RO coproduct credits are accounted for (uncertainty due to modeling choices). We have carried out an extensive data collection to build an LC inventory accounting for parameter uncertainty. Different approaches for carbon stock changes associated with converting set‐aside land to rapeseed cultivation have been considered, which result in different values: from ?0.25 t C/ha.yr (carbon uptake by the soil in tonnes per hectare year) to 0.60 t C/ha.yr (carbon emission). Energy renewability efficiency and GHG emissions of RO are presented, which show the influence of parameter versus scenario uncertainty. Primary energy savings and avoided GHG emissions when RO displaces FD have also been calculated: Avoided GHG emissions show considerably higher uncertainty than energy savings, mainly due to land use (nitrous oxide emissions from soil) and land use conversion (carbon stock changes). Results demonstrate the relevance of applying uncertainty approaches; emphasize the need to reduce uncertainty in the environmental life cycle modeling, particularly GHG emissions calculation; and show the importance of integrating uncertainty into the interpretation of results.     

Green Niche Market Development

This article introduces a multiagent simulation framework for investigating the emergence of niche markets for environmentally innovative products. It clarifies how consumer preferences, business strategy, and government policy interact during market development. The framework allows investigation of the effects of uncertainty and agents' corresponding coping strategies. We describe the model, illustrate how it works when applied to the case of hybrid cars, and analyze results spanning several policy cases and a range of scenarios that make different assumptions about the heterogeneity of agents. Heterogeneity within each agent class strongly influences aggregate outcomes. Innovative firms can create green products in response to or in anticipation of government regulation, but true green niche markets do not emerge unless there are also green consumers. Niche markets do not go mainstream unless scale economies drive costs down to parity with conventional products. Preferred environmental innovation policies change with heterogeneity assumptions.     

Effect of Change of Forest Carbon Storage on Net Carbon Dioxide Balance of Wood Use for Energy in Japan

This study analyzed the net carbon dioxide (CO₂) emission reductions between 2005 and 2050 by using wood for energy under various scenarios of forest management and energy conversion technology in Japan, considering both CO₂ emission reductions from replacement of fossil fuels and changes in carbon storage in forests. According to our model, wood production for energy results in a significant reduction of carbon storage levels in forests (by 46% to 77% in 2050 from the 2005 level). Thus, the net CO₂ emission reduction when wood is used for energy becomes drastically smaller. Conventional tree production for energy increases net CO₂ emissions relative to preserving forests, but fast‐growing tree production may reduce net CO₂ emissions more than preserving forests does. When wood from fast‐growing trees is used to generate electricity with gas turbines, displacing natural gas, the net CO₂ emission reduction from the combination of fast‐growing trees and electricity generation with gas turbines is about 58% of the CO₂ emission reduction from electricity generation from gas turbines alone in 2050, and an energy conversion efficiency of around 20% or more is required to obtain net reductions over the entire period until 2050. When wood is used to produce bioethanol, displacing gasoline, net reductions are realized after 2030, provided that heat energy is recovered from residues from ethanol production. These results show the importance of considering the change in carbon storage when estimating the net CO₂ emission reduction effect of the wood use for energy.     

Data for the Carbon Footprinting of Rendering Operations

This article presents a tool and data for calculation of the carbon footprint of rendering operations in North America, quantifying Scope 1 (direct) and Scope 2 (indirect) greenhouse gas emissions. Scope 3 (life cycle) emissions are not included. According to the sample data, in one year an average‐size rendering plant in North America processes 100,000 tonnes (t) of meat by‐products, fallen animals, and restaurant grease and produces 40,000 t of marketable fats and proteins. A plant of this size emits directly about 20,000 t of carbon dioxide (CO₂), mostly by burning fuels to operate cookers that destroy pathogens, drive off moisture, and separate the fat and protein. Another 4,000 t of CO₂ is emitted by utility companies to provide electricity for the rendering process. These direct and indirect emissions are equivalent to about 30% of the CO₂ that would be released if all of the carbon in the rendered raw material were decomposed into CO₂.     

Uncertainty and Variability in Product Carbon Footprinting

Recent years have seen increasing interest in life cycle greenhouse gas emissions accounting, also known as carbon footprinting, due to drivers such as transportation fuels policy and climate‐related eco‐labels, sometimes called carbon labels. However, it remains unclear whether applications of greenhouse gas accounting, such as carbon labels, are supportable given the level of precision that is possible with current methodology and data. The goal of this work is to further the understanding of quantitative uncertainty assessment in carbon footprinting through a case study of a rackmount electronic server. Production phase uncertainty was found to be moderate (±15%), though with a high likelihood of being significantly underestimated given the limitations in available data for assessing uncertainty associated with temporal variability and technological specificity. Individual components or subassemblies showed varying levels of uncertainty due to differences in parameter uncertainty (i.e., agreement between data sets) and variability between production or use regions. The use phase displayed a considerably higher uncertainty (±50%) than production due to uncertainty in the useful lifetime of the server, variability in electricity mixes in different market regions, and use profile uncertainty. Overall model uncertainty was found to be ±35% for the whole life cycle, a substantial amount given that the method is already being used to set policy and make comparative environmental product declarations. Future work should continue to combine the increasing volume of available data to ensure consistency and maximize the credibility of the methods of life cycle assessment (LCA) and carbon footprinting. However, for some energy‐using products it may make more sense to increase focus on energy efficiency and use phase emissions reductions rather than attempting to quantify and reduce the uncertainty of the relatively small production phase.