Life cycle greenhouse gas emissions of palm oil production by wet and dry extraction processes in Thailand

Purpose

The crude palm oil (CPO) extraction is normally done by a wet extraction process, and wastewater treatment of the wet process emits high levels of greenhouse gases (GHGs). A dry process extracts mixed palm oil (MPO) from palm fruit without using water and has no GHG emissions from wastewater treatment. This work is aimed at determining the GHG emissions of a dry process and at evaluating GHG savings on changing from wet to dry process, including land use change (LUC) effects.

Methods

Life cycle assessment from cradle to gate was used. The raw material is palm fruits. The dry process includes primary production, oil room, and utilities. MPO is the main product, while palm cake and fine palm residue are co-products sold for animal feed. Case studies were undertaken without and with carbon stocks of firewood and of nitrogen recycling at plantations from fronds. Allocations by mass, economic, and heating values were conducted. The trading of GHG emissions from co-products to GHG emissions from animal feed was assessed. The GHG emissions or savings from direct LUC (dLUC) and from indirect LUC (iLUC) effects and for the change from wet to dry process were determined.

Results and discussion

Palm fruit and firewood were the major GHG emission sources. Nitrogen recycling on plantations from fronds significantly affects the GHG emissions. With the carbon stocks, the GHG emissions allocated by energy value were 550 kg CO₂ eq/t MPO. The GHG emissions were affected by ?3 to 37% for the change from wet to dry process. When the plantation area was increased by 1 ha and the palm oil extraction was changed from wet to dry process, and the change included dLUC and iLUC, the GHG savings ranged from ?0.94 to 5.08 t CO₂ eq/ha year. The iLUC was the main GHG emission source. The GHG saving mostly originated from the change of extraction process and from the dLUC effect. Based on the potential use of biodiesel production from oil palm, during 2015–2036 in Thailand, when the extraction process was changed and dLUC and iLUC effects were included, the saving in GHG emissions was estimated to range from ?35,454 to 274,774 t CO₂ eq/year.

Conclusions

The change of palm oil extraction process and the LUC effects could minimize the GHG emissions from the palm oil industry. This advantage encourages developing policies that support the dry extraction process and contribute to sustainable developments in palm oil production.

     

Energy balances and greenhouse gas emissions of palm oil biodiesel in Indonesia

This study presents a cradle‐to‐gate assessment of the energy balances and greenhouse gas (GHG) emissions of Indonesian palm oil biodiesel production, including the stages of land‐use change (LUC), agricultural phase, transportation, milling, biodiesel processing, and comparing the results from different farming systems, including company plantations and smallholder plantations (either out growers or independent growers) in different locations in Kalimantan and Sumatra of Indonesia. The findings demonstrate that there are considerable differences between the farming systems and the locations in net energy yields (43.6–49.2 GJ t^?1 biodiesel yr^?1) as well as GHG emissions (1969.6–5626.4 kg CO_2eq t^?1 biodiesel yr^?1). The output to input ratios are positive in all cases. The largest GHG emissions result from LUC effects, followed by the transesterification, fertilizer production, agricultural production processes, milling, and transportation. Ecosystem carbon payback times range from 11 to 42 years.     

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.     

Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production,Part II: Uncertainty Analysis through Sensitivity Analysis and Scenario Testing

This is the second part of a two‐article series examining California almond production. The part I article describes development of the analytical framework and life cycle–based model and presents typical energy use and greenhouse gas (GHG) emissions for California almonds. This part II article builds on this by exploring uncertainty in the life cycle model through sensitivity and scenario analysis, and by examining temporary carbon storage in the orchard. Sensitivity analysis shows life cycle GHG emissions are most affected by biomass fate and utilization, followed by nitrous oxide emissions rates from orchard soils. Model sensitivity for net energy consumption is highest for irrigation system parameters, followed by biomass fate and utilization. Scenario analysis shows utilization of orchard biomass for electricity production has the greatest potential effect, assuming displacement methods are used for co‐product allocation. Results of the scenario analysis show that 1 kilogram (kg) of almond kernel and associated co‐products are estimated to cause between ?3.12 to 2.67 kg carbon dioxide equivalent (CO₂‐eq) emissions and consume between 27.6 to 52.5 megajoules (MJ) of energy. Co‐product displacement credits lead to avoided emissions of between ?1.33 to 2.45 kg CO₂‐eq and between ?0.08 to 13.7 MJ of avoided energy use, leading to net results of ?1.39 to 3.99 kg CO₂‐eq and 15.3 to 52.6 MJ per kg kernel (net results are calculated by subtracting co‐product credits from the results for almonds and co‐products). Temporary carbon storage in orchard biomass and soils is accounted for by using alternative global warming characterization factors and leads to a 14% to 18% reduction in CO₂‐eq emissions. Future studies of orchards and other perennial cropping systems should likely consider temporary carbon storage.     

The Greenhouse Gas Footprint of China's Food System: An Analysis of Recent Trends and Future Scenarios

Food chain systems (FCSs), which begin in agricultural production and end in consumption and waste disposal, play a significant role in China's rising greenhouse gas (GHG) emissions. This article uses scenario analysis to show China's potential trajectories to a low‐carbon FCS. Between 1996 and 2010, the GHG footprint of China's FCSs increased from 1,308 to 1,618 megatonnes of carbon dioxide equivalent (Mt CO₂‐eq), although the emissions intensity of all food categories, except for aquatic food, recorded steep declines. We project three scenarios to 2050 based on historical trends and plausible shifts in policies and environmental conditions: reference scenario; technology improvement scenario; and low GHG emissions scenario. The reference scenario is based on existing trends and exhibits a large growth in GHG emissions, increasing from 1,585 Mt CO₂‐eq in 2010 to 2,505 Mt CO₂‐eq in 2050. In the technology improvement scenario, emissions growth is driven by rising food demand, but that growth will be counterbalanced by gains in agricultural technology, causing GHG emissions to fall to 1,413 Mt CO₂‐eq by 2050. Combining technology improvement with the shift to healthier dietary patterns, GHG emissions in the low GHG emissions scenario will decline to 946 Mt CO₂‐eq in 2050, a drop of 41.5% compared with the level in 2010. We argue that these are realistic projections and are indeed indicative of China's overall strategy for low‐carbon development. Improving agricultural technology and shifting to a more balanced diet could significantly reduce the GHG footprint of China's FCSs. Furthermore, the transition to a low‐carbon FCS has potential cobenefits for land sustainability and public health.     

A model‐based quantitative assessment of the carbon benefits of introducing iLUC factors in the European Renewable Energy Directive

The European Commission has a mandate from the EU's Renewable Energy and Fuel Quality Directives to propose a methodology, consistent with the best available science, to address indirect land use change (iLUC). One proposed solution to the iLUC problem is the application of iLUC factors in European fuels policy – it is widely expected that should the EU adopt such iLUC factors, they would be based on iLUC modelling using the International Food Policy Research Institute's (IFPRI) MIRAGE model. Taking the iLUC factors from IFPRI MIRAGE as our central estimate, we use Monte Carlo analysis on a simple model of potential biofuel pathways for Europe to assess the likely average carbon saving from three possible European biofuel policy scenarios: no action on iLUC; raised GHG thresholds for direct emissions savings; and the introduction of iLUC factors. We find that without iLUC factors (or some other effective iLUC minimization approach) European biofuel mandates are unlikely to deliver significant GHG emissions benefits in 2020, and have a substantial probability of increasing net GHG emissions. In contrast, the implementation of iLUC factors is likely to significantly increase the carbon savings from EU biofuel policy. With iLUC factors, it is likely that most permitted pathways would conform to the Renewable Energy Directive requirement for a minimum 50% GHG reduction compared to fossil fuels.     

Environmental performance of gasified willow from different lands including land‐use changes

A life‐cycle assessment (LCA) of a low‐input, short rotation coppice (SRC) willow grown on different Danish lands was performed. Woodchips are gasified, producer gas is used for cogeneration of heat and power (CHP), and the ash–char output is applied as soil amendment in the field. A hybrid model was developed for the estimation of greenhouse gas (GHG) emissions from indirect land‐use changes (iLUC) induced by willow cropping on arable land (iLUC_food). For this, area expansion results from a general equilibrium economic model were combined with global LUC trends to differentiate between land transformation (as additional agricultural expansion, in areas with historical deforestation) and occupation (as delayed relaxation, DR, in areas with historical land abandonment) impacts. A biophysical approach was followed to determine the iLUC_feed emissions factor from marginal grassland. Land transformation impacts were derived from latest world deforestation statistics, while a commercial feed mix of equivalent nutritive value was assumed to substitute the displaced grass as fodder. Intensification effects were included in both iLUC factors as additional N‐fertilizer consumption. Finally, DR impacts were considered for abandoned farmland, as a relative C stock loss compared to natural regeneration. ILUC results show that area related GHG emissions are dominant (93% of iLUC_food and 80% of iLUC_feed), transformation being more important (82% of iLUC_food) than occupation (11%) impacts. LCA results show that CHP from willow emits 4047 kg CO₂‐eq (or 0.8 gCO₂‐eq MJ^?1) when grown on arable land, while sequestering 43 745 kg CO₂‐eq (or ?10.4 gCO₂‐eq MJ^?1) when planted on marginal pastureland, and 134 296 kg CO₂‐eq (or ?31.8 gCO₂‐eq MJ^?1) when marginal abandoned land is cultivated. Increasing the bioenergy potential without undesirable iLUC effects, especially relevant regarding biodiversity impacts, requires that part of the marginally used extensive grasslands are released from their current use or energy cropping on abandoned farmland incentivized.     

European renewable energy directive: Critical analysis of important default values and methods for calculating greenhouse gas (GHG) emissions of palm oil biodiesel

Purpose

The aim of this paper is to evaluate assumptions and data used in calculations  related to palm oil produced for biodiesel production relative to the European Renewable Energy Directive (EU-RED). The intent of this paper is not to review all assumptions and data, but rather to evaluate whether the methodology is applied in a consistent way and whether current default values address relevant management practices of palm oil production systems.

Methods

The GHG calculation method provided in Annex V of the EU-RED was used to calculate the GHG-emissions from palm oil production systems. Moreover, the internal nitrogen recycling on the plantation was calculated based on monitoring data in North Sumatra.

Results and discussion

A calculation methodology is detailed in Annex V of the EU-RED. Some important aspects necessary to calculate the GHG emission savings correctly are insufficiently considered, e.g.: ? “Nitrogen recycling” within the plantation due to fronds remaining on the plantation is ignored. The associated organic N-input to the plantation and the resulting nitrous oxide emissions is not considered within the calculations, despite crop residues being taken into account for annual crops in the BIOGRACE tool. ? The calculation of GHG-emissions from residue and waste water treatment is inappropriately implemented despite being a hot-spot for GHG emissions within the life cycle of palm oil and palm oil biodiesel. Additionally, no distinction is made between palm oil and palm kernel oil even though palm kernel oil is rarely used for biodiesel production. ? The allocation procedure does not address the most relevant oil mill management practices. Palm oil mills produce crude palm oil (CPO) in addition either nuts or palm kernels and nut shells. In the first case, the nuts would be treated as co-products and upstream emissions would be allocated based on the energy content; in the second case the kernels would be treated as co-products while the shelöls are considered as waste without upstream emissions. This has a significant impact on the resulst or GHG savings, respectively. ? It is not specified whether indirect GHG emissions from nitrogen oxide emission from the heat and power unit of palm oil mills should be taken into account.

Conclusions and recommendations

In conclusion, the existing calculation methodology described in Annex V of the EU-RED and default values are insufficient for calculating the real GHG emission savings from palm oil and palm oil biodiesel. The current default values do not reflect relevant management practices. Additionally, they protect poor management practices, such as the disposal of empty fruit bunches (EFB), and lead to an overestimation of GHG savings from palm oil biodiesel. A default value for EFB disposal must be introduced because resulting GHG emissions are substantial. Organic nitrogen from fronds must be taken into account when calculating real GHG savings from palm oil biodiesel. Further, more conservative data for FFB yield and fugitive emissions from wastewater treatment should be introduced in order to foster environmental friendly management options. Moreover, credits for bioenergy production from crop residues should be allowed in order to foster the mobilization of currently unused biomass.     

Influence of spatially dependent,modeled soil carbon emission factors on life‐cycle greenhouse gas emissions of corn and cellulosic ethanol

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.     

Environmental implications of the use of agro‐industrial residues for biorefineries: application of a deterministic model for indirect land‐use changes

Biorefining agro‐industrial biomass residues for bioenergy production represents an opportunity for both sustainable energy supply and greenhouse gas (GHG) emissions mitigation. Yet, is bioenergy the most sustainable use for these residues? To assess the importance of the alternative use of these residues, a consequential life cycle assessment (LCA) of 32 energy‐focused biorefinery scenarios was performed based on eight selected agro‐industrial residues and four conversion pathways (two involving bioethanol and two biogas). To specifically address indirect land‐use changes (iLUC) induced by the competing feed/food sector, a deterministic iLUC model, addressing global impacts, was developed. A dedicated biochemical model was developed to establish detailed mass, energy, and substance balances for each biomass conversion pathway, as input to the LCA. The results demonstrated that, even for residual biomass, environmental savings from fossil fuel displacement can be completely outbalanced by iLUC, depending on the feed value of the biomass residue. This was the case of industrial residues (e.g. whey and beet molasses) in most of the scenarios assessed. Overall, the GHGs from iLUC impacts were quantified to 4.1 t CO₂‐eq.ha^?1_demanded yr^?1 corresponding to 1.2–1.4 t CO₂‐eq. t^?1 dry biomass diverted from feed to energy market. Only, bioenergy from straw and wild grass was shown to perform better than the alternative use, as no competition with the feed sector was involved. Biogas for heat and power production was the best performing pathway, in a short‐term context. Focusing on transport fuels, bioethanol was generally preferable to biomethane considering conventional biogas upgrading technologies. Based on the results, agro‐industrial residues cannot be considered burden‐free simply because they are a residual biomass and careful accounting of alternative utilization is a prerequisite to assess the sustainability of a given use. In this endeavor, the iLUC factors and biochemical model proposed herein can be used as templates and directly applied to any bioenergy consequential study involving demand for arable land.     

Life Cycle–based Assessment of Energy Use and Greenhouse Gas Emissions in Almond Production,Part I: Analytical Framework and Baseline Results

This first article of a two‐article series describes a framework and life cycle–based model for typical almond orchard production systems for California, where more than 80% of commercial almonds on the world market are produced. The comprehensive, multiyear, life cycle–based model includes orchard establishment and removal; field operations and inputs; emissions from orchard soils; and transport and utilization of co‐products. These processes are analyzed to yield a life cycle inventory of energy use, greenhouse gas (GHG) emissions, criteria air pollutants, and direct water use from field to factory gate. Results show that 1 kilogram (kg) of raw almonds and associated co‐products of hulls, shells, and woody biomass require 35 megajoules (MJ) of energy and result in 1.6 kg carbon dioxide equivalent (CO₂‐eq) of GHG emissions. Nitrogen fertilizer and irrigation water are the dominant causes of both energy use and GHG emissions. Co‐product credits play an important role in estimating the life cycle environmental impacts attributable to almonds alone; using displacement methods results in net energy and emissions of 29 MJ and 0.9 kg CO₂‐eq/kg. The largest sources of credits are from orchard biomass and shells used in electricity generation, which are modeled as displacing average California electricity. Using economic allocation methods produces significantly different results; 1 kg of almonds is responsible for 33 MJ of energy and 1.5 kg CO₂‐eq emissions. Uncertainty analysis of important parameters and assumptions, as well as temporary carbon storage in orchard trees and soils, are explored in the second article of this two‐part article series.     

What can and can't we say about indirect land‐use change in Brazil using an integrated economic – land‐use change model?

It is commonly recognized that large uncertainties exist in modelled biofuel‐induced indirect land‐use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general methodology to stochastically calculate direct and indirect land‐use change (dLUC and iLUC) caused by an increasing demand for biofuels, with an integrated economic – land‐use change model. We use the global Computable General Equilibrium model MAGNET, connected to the spatially explicit land‐use change model PLUC. We quantify important uncertainties in the modelling chain. Next, dLUC and iLUC projections for Brazil up to 2030 at different spatial scales and the uncertainty herein are assessed. Our results show that cell‐based (5 × 5 km²) probabilities of dLUC range from 0 to 0.77, and of iLUC from 0 to 0.43, indicating that it is difficult to project exactly where dLUC and iLUC will occur, with more difficulties for iLUC than for dLUC. At country level, dLUC area can be projected with high certainty, having a coefficient of variation (cv) of only 0.02, while iLUC area is still uncertain, having a cv of 0.72. The latter means that, considering the 95% confidence interval, the iLUC area in Brazil might be 2.4 times as high or as low as the projected mean. Because this confidence interval is so wide that it is likely to straddle any legislation threshold, our opinion is that threshold evaluation for iLUC indicators should not be implemented in legislation. For future studies, we emphasize the need for provision of quantitative uncertainty estimates together with the calculated LUC indicators, to allow users to evaluate the reliability of these indicators and the effects of their uncertainty on the impacts of land‐use change, such as greenhouse gas emissions.     

Quantifying global greenhouse gas emissions from land‐use change for crop production

Many assessments of product carbon footprint (PCF) for agricultural products omit emissions arising from land‐use change (LUC). In this study, we developed a framework based on IPCC national greenhouse gas inventory methodologies to assess the impacts of LUC from crop production using oil palm, soybean and oilseed rape as examples. Using ecological zone, climate and soil types from the top 20 producing countries, calculated emissions for transitions from natural vegetation to cropland on mineral soils under typical management ranged from ?4.5 to 29.4 t CO₂‐eq ha^?1 yr^?1 over 20 years for oil palm and 1.2–47.5 t CO₂‐eq ha^?1 yr^?1 over 20 years for soybeans. Oilseed rape showed similar results to soybeans, but with lower maximum values because it is mainly grown in areas with lower C stocks. GHG emissions from other land‐use transitions were between 62% and 95% lower than those from natural vegetation for the arable crops, while conversions to oil palm were a sink for C. LUC emissions were considered on a national basis and also expressed per‐tonne‐of‐oil‐produced. Weighted global averages indicate that, depending on the land‐use transition, oil crop production on newly converted land contributes between ?3.1 and 7.0 t CO₂‐eq t oil production^?1 yr^?1 for palm oil, 11.9–50.6 t CO₂‐eq t oil production^?1 yr^?1 for soybean oil, and 7.7–31.4 t CO₂‐eq t oil production^?1 yr^?1 for rapeseed oil. Assumptions made about crop and LUC distribution within countries contributed up to 66% error around the global averages for natural vegetation conversions. Uncertainty around biomass and soil C stocks were also examined. Finer resolution data and information (particularly on land management and yield) could improve reliability of the estimates but the framework can be used in all global regions and represents an important step forward for including LUC emissions in PCFs.     

Estimating the Greenhouse Gas Balance of Individual Gas‐Fired and Oil‐Fired Electricity Plants on a Global Scale

Life cycle greenhouse gas (LC‐GHG) emissions from electricity generated by a specific resource, such as gas and oil, are commonly reported on a country‐by‐country basis. Estimation of variability in LC‐GHG emissions of individual power plants can, however, be particularly useful to evaluate or identify appropriate environmental policy measures. Here, we developed a regression model to predict LC‐GHG emissions per kilowatt‐hour (kWh) of electricity produced by individual gas‐ and oil‐fired power plants across the world. The regression model uses power plant characteristics as predictors, including capacity, age, fuel type (fuel oil or natural gas), and technology type (single or combined cycle) of the plant. The predictive power of the model was relatively high (R² = 81% for predictions). Fuel and technology type were identified as the most important predictors. Estimated emission factors ranged from 0.45 to 1.16 kilograms carbon dioxide equivalents per kilowatt‐hour (kg CO₂‐eq/kWh) and were clearly different between natural gas combined cycle (0.45 to 0.57 kg CO₂‐eq/kWh), natural gas single cycle (0.66 to 0.85 kg CO₂‐eq/kWh), oil combined cycle power plants (0.63 to 0.79 kg CO₂‐eq/kWh), and oil single cycle (0.94 to 1.16 kg CO₂‐eq/kWh). Our results thus indicate that emission data averaged by fuel and technology type can be profitably used to estimate the emissions of individual plants.     

A meta-analysis of the life cycle greenhouse gas balances of microalgae biodiesel

Purpose

Microalgae biodiesel has attracted considerable attention as a potential substitute for fossil fuels and biodiesel from food crops. Nevertheless, its reported climate impacts in the scientific literature vary significantly. This article describes and synthesizes the range of results found in the life cycle assessment (LCA) literature regarding microalgae biodiesel studies to investigate whether particular parameters, e.g. technologies, were associated with higher or lower greenhouse gas (GHG) emissions so that a best practice can be inferred from currently available LCA data and thereby recommended.

Methods

A systematic literature review and meta-regression analysis (MRA) of 36 LCA studies that report on the GHG emissions of microalgae biodiesel was conducted. An assessment of key aspects, including modelling choices and technologies, was performed. Furthermore, MRA models were formulated considering several variables of interest describing both technical and modelling choices to identify the main causes for the variability in GHG emissions per MJ of biodiesel. Variables chosen include: microalgae species; culture medium; cultivation system; source of CO₂; extraction technology; conversion technology; system boundary; geographical scope; inclusion or exclusion of capital goods; and how multifunctionality was handled.

Results and discussion

The reviewed studies altogether reported 308 results ranging from ?0.7 to 3.8 kg CO₂ eq. MJ^?1_biodiesel, portraying 19 different system configurations. Despite the comprehensive range of variables assessed, the models generated could not plausibly explain that the variability in GHG emissions depends either on the technologies considered or on the methodological choices adopted. However, the following relationships could be observed: location in Europe and high oil productivity were associated with lower emissions, whilst dry extraction should be avoided for leading to higher GHG emissions, on average.

Conclusions

There is a large degree of variability within the technologies considered, as well as the methodological choices adopted, so that no robust conclusions could be drawn from the MRA. Notwithstanding, average GHG emissions reported were more than twice as high as fossil diesel and, while there are some studies showing large benefits, none of the various algae technologies performed consistently better than fossil diesel, questioning the climate-mitigation potential of microalgae biodiesel.

     

Life cycle analysis of biochemical cellulosic ethanol under multiple scenarios

Cellulosic ethanol is widely believed to offer substantial environmental advantages over petroleum fuels and grain‐based ethanol, particularly in reducing greenhouse gas emissions from transportation. The environmental impacts of biofuels are largely caused by precombustion activities, feedstock production and conversion facility operations. Life cycle analysis (LCA) is required to understand these impacts. This article describes a field‐to‐blending terminal LCA of cellulosic ethanol produced by biochemical conversion (hydrolysis and fermentation) using corn stover or switchgrass as feedstock. This LCA develops unique models for most elements of the biofuel production process and assigns environmental impact to different phases of production. More than 30 scenarios are evaluated, reflecting a range of feedstock, technology and scale options for near‐term and future facilities. Cellulosic ethanol, as modeled here, has the potential to significantly reduce greenhouse gas (GHG) emissions compared to petroleum‐based liquid transportation fuels, though substantial uncertainty exists. Most of the conservative scenarios estimate GHG emissions of approximately 45–60 g carbon dioxide equivalent per MJ of delivered fuel (g CO₂e MJ^?1) without credit for coproducts, and 20–30 g CO₂e MJ^?1 when coproducts are considered. Under most scenarios, feedstock production, grinding and transport dominate the total GHG footprint. The most optimistic scenarios include sequestration of carbon in soil and have GHG emissions below zero g CO₂e MJ^?1, while the most pessimistic have life‐cycle GHG emissions higher than petroleum gasoline. Soil carbon changes are the greatest source of uncertainty, dominating all other sources of GHG emissions at the upper bound of their uncertainty. Many LCAs of biofuels are narrowly constrained to GHG emissions and energy; however, these narrow assessments may miss important environmental impacts. To ensure a more holistic assessment of environmental performance, a complete life cycle inventory, with over 1100 tracked material and energy flows for each scenario is provided in the online supplementary material for this article.     

Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective

Growing biomass feedstocks from marginal lands is becoming an increasingly attractive choice for producing biofuel as an alternative energy to fossil fuels. Here, we used a biogeochemical model at ecosystem scale to estimate crop productivity and greenhouse gas (GHG) emissions from bioenergy crops grown on marginal lands in the United States. Two broadly tested cellulosic crops, switchgrass, and Miscanthus, were assumed to be grown on the abandoned land and mixed crop‐vegetation land with marginal productivity. Production of biomass and biofuel as well as net carbon exchange and nitrous oxide emissions were estimated in a spatially explicit manner. We found that, cellulosic crops, especially Miscanthus could produce a considerable amount of biomass, and the effective ethanol yield is high on these marginal lands. For every hectare of marginal land, switchgrass and Miscanthus could produce 1.0–2.3 kl and 2.9–6.9 kl ethanol, respectively, depending on nitrogen fertilization rate and biofuel conversion efficiency. Nationally, both crop systems act as net GHG sources. Switchgrass has high global warming intensity (100–390 g CO₂eq l^?1 ethanol), in terms of GHG emissions per unit ethanol produced. Miscanthus, however, emits only 21–36 g CO₂eq to produce every liter of ethanol. To reach the mandated cellulosic ethanol target in the United States, growing Miscanthus on the marginal lands could potentially save land and reduce GHG emissions in comparison to growing switchgrass. However, the ecosystem modeling is still limited by data availability and model deficiencies, further efforts should be made to classify crop‐specific marginal land availability, improve model structure, and better integrate ecosystem modeling into life cycle assessment.     

Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan,Indonesia

Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world’s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia’s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4–211.4 MtCO₂ yr^-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55–60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia’s national emissions mitigation goal, while allowing oil palm area to double.     

Agricultural greenhouse gas mitigation potential globally,in Europe and in the UK: what have we learnt in the last 20 years?

Agricultural lands occupy about 40–50% of the Earth's land surface. Agricultural practices can make a significant contribution at low cost to increasing soil carbon sinks, reducing greenhouse gas (GHG) emissions and contributing biomass feedstocks for energy use. Considering all gases, the global technical mitigation potential from agriculture (excluding fossil fuel offsets from biomass) by 2030 is estimated to be ca. 5500–6000 Mt CO₂‐eq. yr^?1. Economic potentials are estimated to be 1500–1600, 2500–2700 and 4000–4300 Mt CO₂‐eq. yr^?1 at carbon prices of up to $US20, 50 and 100 t CO₂‐eq.^?1, respectively. The value of the global agricultural GHG mitigation at the same three carbon prices is $US32 000, 130 000 and 420 000 million yr^?1, respectively. At the European level, early estimates of soil carbon sequestration potential in croplands were ca. 200 Mt CO₂ yr^?1, but this is a technical potential and is for geographical Europe as far east as the Urals. The economic potential is much smaller, with more recent estimates for the EU27 suggesting a maximum potential of ca. 20 Mt CO₂‐eq. yr^?1. The UK is small in global terms, but a large part of its land area (11 Mha) is used for agriculture. Agriculture accounts for about 7% of total UK GHG emissions. The mitigation potential of UK agriculture is estimated to be ca. 1–2 Mt CO₂‐eq. yr^?1, accounting for less than 1% of UK total GHG emissions.     

Regional variations in life cycle greenhouse gas emissions of canola‐derived jet fuel produced in western Canada

This study investigates the life cycle GHG emissions of jet fuel produced via the hydroprocessed esters and fatty acids (HEFA) pathway from canola grown in western Canada, with a focus on characterizing regional influences on emissions. We examine the effects of geographic variations in soil type, agricultural inputs, farming practices, and direct land use changes on life cycle GHG emissions. We utilize GREET 2016 but replace default feedstock production inputs with geographically representative data for canola production across eight western Canadian regions (representing 99% of Canada's canola production) and replace the default conversion process with data from a novel process model previously developed in ASPEN in our research group wherein oil extraction is integrated with the HEFA‐based fuel production process. Although canola production inputs and yields vary across the regions, resulting life cycle GHG emissions are similar if effects of land use and land management changes (LMC) are not included; 44–48 g CO₂e/MJ for the eight regions (45%–50% reduction compared to petroleum jet fuel). Results are considerably more variable, 16–58 g CO₂e/MJ, when including effects of land use and LMC directly related to conversion of lands from other uses to canola production (34%–82% reduction compared to petroleum jet fuel). We establish the main sources of emissions in the life cycle of canola jet fuel (N‐fertilizer and related emissions, fuel production), identify that substantially higher emissions may occur when using feedstock sourced from regions where conversion of forested land to cropland had occurred, and identify benefits of less intense tillage practices and increased use of summerfallow land. The methods and findings are relevant in jurisdictions internationally that are incorporating GHG emissions reductions from aviation fuels in a low carbon fuel market or legislating carbon intensity reduction requirements.