Environmental Damage Assessment of Carbon Capture and Storage

An end‐point life cycle impact assessment is used to evaluate the damages of electricity generation from fossil fuel‐based power plants with carbon dioxide capture and storage (CCS) technology. Pulverized coal (PC), integrated gasification combined cycle (IGCC), and natural gas combined cycle (NGCC) power plants are assessed for carbon dioxide (CO₂) capture, pipeline transport, and storage in a geological formation. Results show that the CCS systems reduce the climate change‐related damages but increase the damages from toxicity, acidification, eutrophication, and resource consumption. Based on the currently available damage calculation methods, it is concluded that the benefit of reducing damage from climate change is larger than the increases in other damage categories, such as health effects from particulates or toxic chemicals. CCS significantly reduces the overall environmental damage, with a net reduction of 60% to 70% in human health damage and 65% to 75% in ecosystem damage. Most of the damage is due to fuel production and combustion processes. The energy and infrastructure demands of CCS cause increases in the depletion of natural resources by 33% for PC, 19% for IGCC, and 18% for NGCC power plants, mostly due to increased fossil fuel consumption.     

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.     

Modeling Corn Ethanol and Climate

New fuel regulations based on life cycle greenhouse gas (GHG) emissions have focused renewed attention on life cycle models of biofuels. The BESS model estimates 25% lower life cycle GHG emissions for corn ethanol than does the well-known GREET model, which raises questions about which model is more accurate. I develop a life cycle metamodel to compare the GREET and BESS models in detail and to explain why the results from these models diverge. I find two main reasons for the divergence: (1) BESS models a more efficient biorefinery than is modeled in the cases to which its results have been compared, and (2) in several instances BESS fails to properly count upstream emissions. Adjustments to BESS to account for these differences raise the estimated global warming intensity (not including land use change) of the corn ethanol pathway considered in that model from 45 to 61 g CO₂e MJ⁻¹. Adjusting GREET to use BESS's biorefinery performance and coproduct credit assumptions reduces the GREET estimate from 64 to 61 g CO₂e MJ⁻¹. Although this analysis explains the gap between the two models, both models would be improved with better data on corn production practices and by better treatment of agricultural inputs.     

Improvements in Life Cycle Energy Efficiency and Greenhouse Gas Emissions of Corn-Ethanol

Corn-ethanol production is expanding rapidly with the adoption of improved technologies to increase energy efficiency and profitability in crop production, ethanol conversion, and coproduct use. Life cycle assessment can evaluate the impact of these changes on environmental performance metrics. To this end, we analyzed the life cycles of corn-ethanol systems accounting for the majority of U.S. capacity to estimate greenhouse gas (GHG) emissions and energy efficiencies on the basis of updated values for crop management and yields, biorefinery operation, and coproduct utilization. Direct-effect GHG emissions were estimated to be equivalent to a 48% to 59% reduction compared to gasoline, a twofold to threefold greater reduction than reported in previous studies. Ethanol-to-petroleum output/input ratios ranged from 10:1 to 13:1 but could be increased to 19:1 if farmers adopted high-yield progressive crop and soil management practices. An advanced closed-loop biorefinery with anaerobic digestion reduced GHG emissions by 67% and increased the net energy ratio to 2.2, from 1.5 to 1.8 for the most common systems. Such improved technologies have the potential to move corn-ethanol closer to the hypothetical performance of cellulosic biofuels. Likewise, the larger GHG reductions estimated in this study allow a greater buffer for inclusion of indirect-effect land-use change emissions while still meeting regulatory GHG reduction targets. These results suggest that corn-ethanol systems have substantially greater potential to mitigate GHG emissions and reduce dependence on imported petroleum for transportation fuels than reported previously.     

Contribution of N2O to the greenhouse gas balance of first-generation biofuels

In this study, we analyze the impact of fertilizer‐ and manure‐induced N₂O emissions due to energy crop production on the reduction of greenhouse gas (GHG) emissions when conventional transportation fuels are replaced by first‐generation biofuels (also taking account of other GHG emissions during the entire life cycle). We calculate the nitrous oxide (N₂O) emissions by applying a statistical model that uses spatial data on climate and soil. For the land use that is assumed to be replaced by energy crop production (the ‘reference land‐use system’), we explore a variety of options, the most important of which are cropland for food production, grassland, and natural vegetation. Calculations are also done in the case that emissions due to energy crop production are fully additional and thus no reference is considered. The results are combined with data on other emissions due to biofuels production that are derived from existing studies, resulting in total GHG emission reduction potentials for major biofuels compared with conventional fuels. The results show that N₂O emissions can have an important impact on the overall GHG balance of biofuels, though there are large uncertainties. The most important ones are those in the statistical model and the GHG emissions not related to land use. Ethanol produced from sugar cane and sugar beet are relatively robust GHG savers: these biofuels change the GHG emissions by −103% to −60% (sugar cane) and −58% to −17% (sugar beet), compared with conventional transportation fuels and depending on the reference land‐use system that is considered. The use of diesel from palm fruit also results in a relatively constant and substantial change of the GHG emissions by −75% to −39%. For corn and wheat ethanol, the figures are −38% to 11% and −107% to 53%, respectively. Rapeseed diesel changes the GHG emissions by −81% to 72% and soybean diesel by −111% to 44%. Optimized crop management, which involves the use of state‐of‐the‐art agricultural technologies combined with an optimized fertilization regime and the use of nitrification inhibitors, can reduce N₂O emissions substantially and change the GHG emissions by up to −135 percent points (pp) compared with conventional management. However, the uncertainties in the statistical N₂O emission model and in the data on non‐land‐use GHG emissions due to biofuels production are large; they can change the GHG emission reduction by between −152 and 87 pp.     

Combined MFA-LCA for Analysis of Wastewater Pipeline Networks

Oslo's wastewater pipeline network has an aging stock of concrete, steel, and polyvinyl chloride (PVC) pipelines, which calls for a good portion of expenditures to be directed toward maintenance and investments in rehabilitation. The stock, as it is in 2008, is a direct consequence of the influx of pipelines of different sizes, lengths, and materials of construction into the system over the years. A material flow analysis (MFA) facilitates an analysis of the environmental impacts associated with the manufacture, installation, operation, maintenance, rehabilitation, and retirement of the pipelines. The forecast of the future flows of materials—which, again, is highly interlinked with the historic flows—provides insight into the likely future environmental impacts. This will enable decision makers keen on alleviating such impacts to think along the lines of eco-friendlier processes and technologies or simply different ways of doing business. Needless to say, the operation and maintenance phase accounts for the major bulk of emissions and calls for energy-efficient approaches to this phase of the life cycle, even as manufacturers strive to make their processes energy-efficient and attempt to include captive renewable energy in their total energy consumption. This article focuses on the life cycle greenhouse gas emissions associated with the wastewater pipeline network in the city of Oslo.