Reassessment of Life Cycle Greenhouse Gas Emissions for Soybean Biodiesel

Reducing life cycle greenhouse gas emissions of corn ethanol by integrating biomass to produce heat and power at ethanol plants

Life cycle greenhouse gas emissions impacts of the adoption of the EU Directive on biofuels in Spain. Effect of the import of raw materials and land use changes

Aluminum production is a major energy consumer and important source of greenhouse gas (GHG) emissions globally. Estimation of the energy consumption and GHG emissions caused by aluminum production in China has attracted widespread attention because China produces more than half of the global aluminum. This paper conducted life cycle (LC) energy consumption and GHG emissions analysis of primary and recycled aluminum in China for the year 2020, considering the provincial differences on both the scale of self-generated electricity consumed in primary aluminum production and the generation source of grid electricity. Potentials for energy saving and GHG emissions reductions were also investigated. The results indicate that there are 157,207 MJ of primary fossil energy (PE) consumption and 15,947 kg CO2-eq of GHG emissions per ton of primary aluminum ingot production in China, with the LC GHG emissions as high as 1.5–3.5 times that of developed economies. The LC PE consumption and GHG emissions of recycled aluminum are very low, only 7.5% and 5.3% that of primary aluminum, respectively. Provincial-level results indicate that the LC PE and GHG emissions intensities of primary aluminum in the main production areas are generally higher while those of recycled aluminum are lower in the main production areas. LC PE consumption and GHG emissions can be significantly reduced by decreasing electricity consumption, self-generated electricity management, low-carbon grid electricity development, and industrial relocation. Based on this study, policy suggestions for China’s aluminum industry are proposed. Recycled aluminum industry development, restriction of self-generated electricity, low-carbon electricity utilization, and industrial relocation should be promoted as they are highly helpful for reducing the LC PE consumption and GHG emissions of the aluminum industry. In addition, it is recommended that the central government considers the differences among provinces when designing and implementing policies.

The life cycle greenhouse gas (GHG) emissions induced by increased biofuel consumption are highly uncertain: individual estimates vary from each other and each has a wide intrinsic error band. Using a reduced-form model, we estimated that the bounding range for emissions from indirect land-use change (ILUC) from US corn ethanol expansion was 10 to 340 g CO(2) MJ(-1). Considering various probability distributions to model parameters, the broadest 95% central interval, i.e., between the 2.5 and 97.5%ile values, ranged from 21 to 142 g CO(2)e MJ(-1). ILUC emissions from US corn ethanol expansion thus range from small, but not negligible, to several times greater than the life cycle emissions of gasoline. The ILUC emissions estimates of 30 g CO(2) MJ(-1) for the California Air Resources Board and 34 g CO(2)e MJ(-1) by USEPA (for 2022) are at the low end of the plausible range. The lack of data and understanding (epistemic uncertainty) prevents convergence of judgment on a central value for ILUC emissions. The complexity of the global system being modeled suggests that this range is unlikely to narrow substantially in the near future. Fuel policies that require narrow bounds around point estimates of life cycle GHG emissions are thus incompatible with current and anticipated modeling capabilities. Alternative policies that address the risks associated with uncertainty are more likely to achieve GHG reductions.

Exploring impacts of process technology development and regional factors on life cycle greenhouse gas emissions of corn stover ethanol

The decarbonization of regional electricity systems is a critical enabler of broader economy-wide decarbonization strategies and has motivated robust research on how to decarbonize electricity systems at minimum monetary cost. Since these efforts often focus on the operation of electricity systems, however, they do not account for emissions of the full life cycle associated with different resources. Different resource mixes can achieve a similar level of apparent decarbonization through operational emissions, while achieving very different levels of life cycle greenhouse gas (GHG) emissions reductions. To explore these differences, we model the expansion of the California electricity system from 2030 to 2045 using a simplified electricity dispatch model to investigate how the planning of future electricity systems may differ between prioritizing minimum cost versus minimum life cycle GHG emissions under a common target for operational GHG reductions. We find that explicitly planning for minimum life cycle GHG emissions yields an additional 1.6%–2.0% reduction in annual life cycle GHG emissions at a cost penalty of 5.1%–6.9% and that electricity resource mixes that minimize life cycle GHG emissions tend to favor high capacity factor zero-carbon resources and long-duration storage compared to a minimum cost approach. Comparatively, we find that aggressive supply chain decarbonization of generation and storage technologies reduces life cycle GHG emissions of electricity supplies by 3.0% to 14% and combining both increases these reductions to 5.0% to 16%. Further, we find that applying a carbon tax to minimum cost-based capacity expansion can incentivize planning to account for life cycle GHG emissions. Our results indicate that a planning approach focused on minimizing life cycle GHG emissions may not be palatable, but significant reductions in life cycle emissions can be realized through conventional mechanisms like carbon taxes, import standards, and targeted supply chain decarbonization.

The decarbonization of regional electricity systems is a critical enabler of broader economy-wide decarbonization strategies and has motivated robust research on how to decarbonize electricity systems at minimum monetary cost. Since these efforts often focus on the operation of electricity systems, however, they do not account for emissions of the full life cycle associated with different resources. Different resource mixes can achieve a similar level of decarbonization apparent decarbonization through operational emissions, while achieving very different levels of life cycle greenhouse gas (GHG) emissions reductions. To explore these differences, we model the expansion of the California electricity system from 2030 to 2045 using a simplified electricity dispatch model to investigate how the planning of future electricity systems may differ between prioritizing minimum cost versus minimum life cycle GHG emissions under a common target for operational GHG reductions. We find that explicitly planning for minimum life cycle GHG emissions yields an additional 1.6-2.0% reduction in annual life cycle GHG emissions at a cost penalty of 3.2–9.6% and that electricity resource mixes that minimize life cycle GHG emissions tend to favor high capacity factor zero-carbon resources and long-duration storage compared to a minimum cost approach. Comparatively, we find that aggressive supply chain decarbonization of generation and storage technologies reduces life cycle GHG emissions of electricity supplies by 3.0% to 14% and combining both increases these reductions to 5.0% to 16%. Further, we find that applying a carbon tax to minimum cost-based capacity expansion can incentivize planning to account for life cycle GHG emissions. Our results indicate that a planning approach focused on minimizing life cycle GHG emissions may not be palatable, but significant reductions in life cycle emissions can be realized through conventional mechanisms like carbon taxes, import standards, and targeted supply chain decarbonization.

Despite the ever-growing body of life cycle assessment (LCA) literature on electricity generation technologies, inconsistent methods and assumptions hamper comparison across studies and pooling of published results. Synthesis of the body of previous research is necessary to generate robust results to assess and compare environmental performance of different energy technologies for the benefit of policy makers, managers, investors, and citizens. With funding from the U.S. Department of Energy, the National Renewable Energy Laboratory initiated the LCA Harmonization Project in an effort to rigorously leverage the numerous individual studies to develop collective insights. The goals of this project were to: (1) understand the range of published results of LCAs of electricity generation technologies, (2) reduce the variability in published results that stem from inconsistent methods and assumptions, and (3) clarify the central tendency of published estimates to make the collective results of LCAs available to decision makers in the near term. The LCA Harmonization Project's initial focus was evaluating life cycle greenhouse gas (GHG) emissions from electricity generation technologies. Six articles from this first phase of the project are presented in a special supplemental issue of the Journal of Industrial Ecology on Meta-Analysis of LCA: coal (Whitaker et al. 2012), concentratingmore » solar power (Burkhardt et al. 2012), crystalline silicon photovoltaics (PVs) (Hsu et al. 2012), thin-film PVs (Kim et al. 2012), nuclear (Warner and Heath 2012), and wind (Dolan and Heath 2012). Harmonization is a meta-analytical approach that addresses inconsistency in methods and assumptions of previously published life cycle impact estimates. It has been applied in a rigorous manner to estimates of life cycle GHG emissions from many categories of electricity generation technologies in articles that appear in this special supplemental supplemental issue, reducing the variability and clarifying the central tendency of those estimates in ways useful for decision makers and analysts. Each article took a slightly different approach, demonstrating the flexibility of the harmonization approach. Each article also discusses limitations of the current research, and the state of knowledge and of harmonization, pointing toward a path of extending and improving the meta-analysis of LCAs.« less

Plug-in hybrid electric vehicle (PHEV) technology has the potential to reduce operating cost, greenhouse gas (GHG) emissions, and petroleum consumption in the transportation sector. However, the net effects of PHEVs depend critically on vehicle design, battery technology, and charging frequency. To examine these implications, we develop an optimization model integrating vehicle physics simulation, battery degradation data, and U.S. driving data. The model identifies optimal vehicle designs and allocation of vehicles to drivers for minimum net life cycle cost, GHG emissions, and petroleum consumption under a range of scenarios. We compare conventional and hybrid electric vehicles (HEVs) to PHEVs with equivalent size and performance (similar to a Toyota Prius) under urban driving conditions. We find that while PHEVs with large battery packs minimize petroleum consumption, a mix of PHEVs with packs sized for ∼25–50 miles of electric travel under the average U.S. grid mix (or ∼35–60 miles under decarbonized grid scenarios) produces the greatest reduction in life cycle GHG emissions. Life cycle cost and GHG emissions are minimized using high battery swing and replacing batteries as needed, rather than designing underutilized capacity into the vehicle with corresponding production, weight, and cost implications. At 2008 average U.S. energy prices, Li-ion battery pack costs must fall below $590/kW h at a 5% discount rate or below $410/kW h at a 10% rate for PHEVs to be cost competitive with HEVs. Carbon allowance prices offer little leverage for improving cost competitiveness of PHEVs. PHEV life cycle costs must fall to within a few percent of HEVs in order to offer a cost-effective approach to GHG reduction.

A life-cycle assessment (LCA) of corn ethanol was conducted to determine the reduction in the life-cycle greenhouse gas (GHG) emissions of corn ethanol compared to gasoline by integrating biomass fuels in a 190 million liter (50 million gallon) per year dry-grind corn ethanol plant to replace fossil fuels (natural gas and grid electricity). The biomass fuels studied are corn stover and ethanol co-products [dried distillers grains with solubles (DDGS), and syrup (solubles portion of DDGS)]. The biomass conversion technologies/systems considered are process heat (PH) only systems, combined heat and power (CHP) systems, and biomass integrated gasification combined cycle (BIGCC) systems. The key inventory components of the LCA are corn production, stover production, ethanol production, fertilizer inputs, truck transport, co-product credits, ethanol transport to blending, biomass fuel conversion systems, and combustion of anhydrous ethanol (E100). The life-cycle GHG emission reduction for corn ethanol compared to gasoline (97.7 g CO2e/MJ gasoline) is 42.5% for PH with natural gas, 61.3% for PH with corn stover, 82.2% for CHP with corn stover, 81.6% for IGCC with natural gas, 127.7% for BIGCC with corn stover, and 119.1% for BIGCC with syrup and stover. These GHG emission estimates do not include indirect land use change effects. GHG emission reductions for CHP, IGCC, and BIGCC include power sent to the grid which replaces electricity from coal. BIGCC results in greater reductions in GHG emissions than IGCC with natural gas because biomass is substituted for fossil fuels. In addition, underground sequestration of CO2 gas from the ethanol plant’s fermentation tank could further reduce the life-cycle GHG emission of corn ethanol by 31.5% compared to gasoline.

A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies

Impacts of alternative fuel combustion in cement manufacturing: Life cycle greenhouse gas, biogenic carbon, and criteria air contaminant emissions

Introducing demand to supply ratio as a new metric for understanding life cycle greenhouse gas (GHG) emissions from rainwater harvesting systems

Replacement of fossil fuels with sustainably produced biomass crops for energy purposes has the potential to make progress in addressing climate change concerns, nonrenewable resource use, and energy security. The perennial grass Miscanthus is a dedicated energy crop candidate being field tested in Ontario, Canada, and elsewhere. Miscanthus could potentially be grown in areas of the province that differ substantially in terms of agricultural land class, environmental factors and current land use. These differences could significantly affect Miscanthus yields, input requirements, production practices, and the types of crops being displaced by Miscanthus establishment. This study assesses implications on life cycle greenhouse gas (GHG) emissions of these differences through evaluating five Miscanthus production scenarios within the Ontario context. Emissions associated with electricity generation with Miscanthus pellets in a hypothetically retrofitted coal generating station are examined. Indirect land use change impacts are not quantified but are discussed. The net life cycle emissions for Miscanthus production varied greatly among scenarios (−90–170 kg CO2eq per oven dry tonne of Miscanthus bales at the farm gate). In some cases, the carbon stock dynamics of the agricultural system offset the combined emissions of all other life cycle stages (i.e., production, harvest, transport, and processing of biomass). Yield and soil C of the displaced agricultural systems are key parameters affecting emissions. The systems with the highest potential to provide reductions in GHG emissions are those with high yields, or systems established on land with low soil carbon. All scenarios have substantially lower life cycle emissions (−20–190 g CO2eq kWh−1) compared with coal‐generated electricity (1130 g CO2eq kWh−1). Policy development should consider the implication of land class, environmental factors, and current land use on Miscanthus production.

We suggest a 2D-plot representation combined with life cycle greenhouse gas (GHG) emissions and life cycle cost for various energy conversion technologies. In general, life cycle assessment (LCA) not only analyzes at the use phase of a specific technology, but also covers widely related processes of before and after its use. We use life cycle GHG emissions and life cycle cost (LCC) to compare the energy conversion process for eight resources such as coal, natural gas, nuclear power, hydro power, geothermal power, wind power, solar thermal power, and solar photovoltaic (PV) power based on the reported LCA and LCC data. Among the eight sources, solar PV and nuclear power exhibit the highest and the lowest LCCs, respectively. On the other hand, coal and wind power locate the highest and the lowest life cycle GHG emissions. In addition, we used the 2D plot to show the life cycle performance of GHG emissions and LCCs simultaneously and realized a correlation that life cycle GHG emission is largely inversely proportional to the corresponding LCCs. It means that an expensive energy source with high LCC tends to have low life cycle GHG emissions, or is environmental friendly. For future study, we will measure the technological maturity of the energy sources to determine the direction of the specific technology development based on the 2D plot of LCCs versus life cycle GHG emissions.