Addressing global environmental impacts including land use change in life cycle optimization: Studies on biofuels

BackgroundThe greenhouse gas (GHG) emissions that may accompany land-use change (LUC) from increased biofuel feedstock production are a source of debate in the discussion of drawbacks and advantages of biofuels. Estimates of LUC GHG emissions focus mainly on corn ethanol and vary widely. Increasing the understanding of LUC GHG impacts associated with both corn and cellulosic ethanol will inform the on-going debate concerning their magnitudes and sources of variability.ResultsIn our study, we estimate LUC GHG emissions for ethanol from four feedstocks: corn, corn stover, switchgrass, and miscanthus. We use new computable general equilibrium (CGE) results for worldwide LUC. U.S. domestic carbon emission factors are from state-level modelling with a surrogate CENTURY model and U.S. Forest Service data. This paper investigates the effect of several key domestic lands carbon content modelling parameters on LUC GHG emissions. International carbon emission factors are from the Woods Hole Research Center. LUC GHG emissions are calculated from these LUCs and carbon content data with Argonne National Laboratory’s Carbon Calculator for Land Use Change from Biofuels Production (CCLUB) model. Our results indicate that miscanthus and corn ethanol have the lowest (−10 g CO2e/MJ) and highest (7.6 g CO2e/MJ) LUC GHG emissions under base case modelling assumptions. The results for corn ethanol are lower than corresponding results from previous studies. Switchgrass ethanol base case results (2.8 g CO2e/MJ) were the most influenced by assumptions regarding converted forestlands and the fate of carbon in harvested wood products. They are greater than miscanthus LUC GHG emissions because switchgrass is a lower-yielding crop. Finally, LUC GHG emissions for corn stover are essentially negligible and insensitive to changes in model assumptions.ConclusionsThis research provides new insight into the influence of key carbon content modelling variables on LUC GHG emissions associated with the four bioethanol pathways we examined. Our results indicate that LUC GHG emissions may have a smaller contribution to the overall biofuel life cycle than previously thought. Additionally, they highlight the need for future advances in LUC GHG emissions estimation including improvements to CGE models and aboveground and belowground carbon content data.

BackgroundThe availability of feedstock options is a key to meeting the volumetric requirement of 136.3 billion liters of renewable fuels per year beginning in 2022, as required in the US 2007 Energy Independence and Security Act. Life-cycle greenhouse gas (GHG) emissions of sorghum-based ethanol need to be assessed for sorghum to play a role in meeting that requirement.ResultsMultiple sorghum-based ethanol production pathways show diverse well-to-wheels (WTW) energy use and GHG emissions due to differences in energy use and fertilizer use intensity associated with sorghum growth and differences in the ethanol conversion processes. All sorghum-based ethanol pathways can achieve significant fossil energy savings. Relative to GHG emissions from conventional gasoline, grain sorghum-based ethanol can reduce WTW GHG emissions by 35% or 23%, respectively, when wet or dried distillers grains with solubles (DGS) is the co-product and fossil natural gas (FNG) is consumed as the process fuel. The reduction increased to 56% or 55%, respectively, for wet or dried DGS co-production when renewable natural gas (RNG) from anaerobic digestion of animal waste is used as the process fuel. These results do not include land-use change (LUC) GHG emissions, which we take as negligible. If LUC GHG emissions for grain sorghum ethanol as estimated by the US Environmental Protection Agency (EPA) are included (26 g CO2e/MJ), these reductions when wet DGS is co-produced decrease to 7% or 29% when FNG or RNG is used as the process fuel. Sweet sorghum-based ethanol can reduce GHG emissions by 71% or 72% without or with use of co-produced vinasse as farm fertilizer, respectively, in ethanol plants using only sugar juice to produce ethanol. If both sugar and cellulosic bagasse were used in the future for ethanol production, an ethanol plant with a combined heat and power (CHP) system that supplies all process energy can achieve a GHG emission reduction of 70% or 72%, respectively, without or with vinasse fertigation. Forage sorghum-based ethanol can achieve a 49% WTW GHG emission reduction when ethanol plants meet process energy demands with CHP. In the case of forage sorghum and an integrated sweet sorghum pathway, the use of a portion of feedstock to fuel CHP systems significantly reduces fossil fuel consumption and GHG emissions.ConclusionsThis study provides new insight into life-cycle energy use and GHG emissions of multiple sorghum-based ethanol production pathways in the US. Our results show that adding sorghum feedstocks to the existing options for ethanol production could help in meeting the requirements for volumes of renewable, advanced and cellulosic bioethanol production in the US required by the EPA’s Renewable Fuel Standard program.

Land use change implications for large-scale cultivation of algae feedstocks in the United States Gulf Coast

Bio-sustainable aviation fuels (bio-SAFs) are an important pillar of the aviation sector decarbonisation strategy in the mid-term. Here we assess the induced Land-Use Change (LUC) implications of producing bio-SAFs in Brazil under different assumptions of forest conservation governance. We evaluate four bio-SAF routes via two main pathways: the Alcohol-to-Jet (ATJ) and the Hydroprocessed Esters and Fatty Acids (HEFA) syntheses. We chose the most promising agriculture-based feedstocks to produce bio-SAFs in all five macro-regions of Brazil, including sugarcane and maize ethanol to jet and palm and macaw HEFA routes. To this end, we calculated future projections of air transport demand in Brazil and used the Brazilian Land Use and Energy Systems integrated assessment model to estimate LUC greenhouse gas (GHG) emissions within five different levels of bio-SAF blends (10% to 50% of total aviation fuel demand) for each bio-SAFs evaluated. Estimated cumulated emissions vary widely, ranging from a carbon sequestration of −286.8 gCO2e.MJ−1 for a 10% blend of maize ATJ under a controlled deforestation scenario to a release of 15.0 gCO2e.MJ−1 for a 40% blend of high productivity macaw oil HEFA considering historical deforestation rates in the country. Results are highly sensitive to deforestation rate parameters, volume of bio-SAFs produced, the type of feedstock used, and methodological assumptions. Negative LUC GHG emissions were found under controlled deforestation assumptions and in low blends of bio-SAFs for maize and sugarcane ATJ routes. Under historical deforestation rates, the LUC GHG emissions are higher. Bio-SAF can be beneficial to reduce GHG emissions if effective land conservation policies are implemented. Therefore, large-scale bio-SAF production from sugar crops in Brazil may play an important role in the decarbonisation of the aviation sector if coupled with successful strategies to control deforestation. Additionally, when imposing bio-SAF demand, other biofuels demand reduces under the model optimal solution due to land restrictions.

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.

Converting land to biofuel feedstock production incurs changes in soil organic carbon (SOC) that can influence biofuel life‐cycle greenhouse gas (GHG) emissions. Estimates of these land use change (LUC) and life‐cycle GHG emissions affect biofuels' attractiveness and eligibility under a number of renewable fuel policies in the USA and abroad. Modeling was used to refine the spatial resolution and depth extent of domestic estimates of SOC change for land (cropland, cropland pasture, grassland, and forest) conversion scenarios to biofuel crops (corn, corn stover, switchgrass, Miscanthus, poplar, and willow) at the county level in the USA. Results show that in most regions, conversions from cropland and cropland pasture to biofuel crops led to neutral or small levels of SOC sequestration, while conversion of grassland and forest generally caused net SOC loss. SOC change results were incorporated into the Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (GREET) model to assess their influence on life‐cycle GHG emissions of corn and cellulosic ethanol. Total LUC GHG emissions (g CO2eq MJ−1) were 2.1–9.3 for corn‐, −0.7 for corn stover‐, −3.4 to 12.9 for switchgrass‐, and −20.1 to −6.2 for Miscanthus ethanol; these varied with SOC modeling assumptions applied. Extending the soil depth from 30 to 100 cm affected spatially explicit SOC change and overall LUC GHG emissions; however, the influence on LUC GHG emission estimates was less significant in corn and corn stover than cellulosic feedstocks. Total life‐cycle GHG emissions (g CO2eq MJ−1, 100 cm) were estimated to be 59–66 for corn ethanol, 14 for stover ethanol, 18–26 for switchgrass ethanol, and −7 to −0.6 for Miscanthus ethanol. The LUC GHG emissions associated with poplar‐ and willow‐derived ethanol may be higher than that for switchgrass ethanol due to lower biomass yield.

Many of the sustainability concerns of bioenergy are related to direct or indirect land use change (LUC) resulting from bioenergy feedstock production. The environmental and socio‐economic impacts of LUC highly depend on the site‐specific biophysical and socio‐economic conditions. The objective of this study is to spatiotemporally assess the potential LUC dynamics resulting from an increased biofuel demand, the related greenhouse gas (GHG) emissions, and the potential effect of LUC mitigation measures. This assessment is demonstrated for LUC dynamics in Brazil towards 2030, considering an increase in the global demand for bioethanol as well as other agricultural commodities. The potential effects of three LUC mitigation measures (increased agricultural productivity, shift to second‐generation ethanol, and strict conservation policies) are evaluated by using a scenario approach. The novel modelling framework developed consists of the global Computable General Equilibrium model MAGNET, the spatiotemporal land use allocation model PLUC, and a GIS‐based carbon module. The modelling simulations illustrate where LUC as a result of an increased global ethanol demand (+26 × 109 L ethanol production in Brazil) is likely to occur. When no measures are taken, sugar cane production is projected to expand mostly at the expense of agricultural land which subsequently leads to the loss of natural vegetation (natural forest and grass and shrubland) in the Cerrado and Amazon. The related losses of above and below ground biomass and soil organic carbon result in the average emission of 26 g CO2‐eq/MJ bioethanol. All LUC mitigation measures show potential to reduce the loss of natural vegetation (18%–96%) as well as the LUC‐related GHG emissions (7%–60%). Although there are several uncertainties regarding the exact location and magnitude of LUC and related GHG emissions, this study shows that the implementation of LUC mitigation measures could have a substantial contribution to the reduction of LUC‐related emissions of bioethanol. However, an integrated approach targeting all land uses is required to obtain substantial and sustained LUC‐related GHG emission reductions in general.

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

Life cycle assessment of primary energy demand and greenhouse gas (GHG) emissions of four propylene production pathways in China

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

Life-cycle analysis (LCA) is an important tool used to assess the energy and environmental impacts of biofuels. Here, we review biofuel LCA methodology and its application in transportation fuel regulations in the United States, the European Union, and the United Kingdom. We examine the application of LCA to the production of ethanol from corn, sugarcane, corn stover, switchgrass, and miscanthus. A discussion of methodological choices such as co-product handling techniques in biofuel LCA is also provided. Further, we discuss the estimation of greenhouse gas (GHG) emissions of land use changes (LUC) potentially caused by biofuels, which can significantly influence LCA results. Finally, we provide results from LCAs of ethanol from various sources. Regardless of feedstock, bioethanol offers reduced GHG emissions over fossil-derived gasoline, even when LUC GHG emissions are included. This is mainly caused by displacement of fossil carbon in gasoline with biogenic carbon in ethanol. Of the ethanol pathways examined, corn ethanol has the greatest life-cycle GHG emissions and offers 30% reduction in life-cycle GHG emissions as compared to gasoline when LUC GHG emissions are included. Miscanthus ethanol demonstrates the highest life-cycle GHG emissions reductions compared to gasoline, 109%, when LUC GHG emissions are included.

Impact of agricultural-based biofuel production on greenhouse gas emissions from land-use change: Key modelling choices

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.

Life cycle greenhouse gas emissions assessment: converting an early retirement coal-fired power plant to a biomass power plant

Life cycle greenhouse gas emissions and freshwater consumption of liquefied Marcellus shale gas used for international power generation