Consensus,uncertainties and challenges for perennial bioenergy crops and land use

Perennial bioenergy crops have significant potential to reduce greenhouse gas (GHG) emissions and contribute to climate change mitigation by substituting for fossil fuels; yet delivering significant GHG savings will require substantial land‐use change, globally. Over the last decade, research has delivered improved understanding of the environmental benefits and risks of this transition to perennial bioenergy crops, addressing concerns that the impacts of land conversion to perennial bioenergy crops could result in increased rather than decreased GHG emissions. For policymakers to assess the most cost‐effective and sustainable options for deployment and climate change mitigation, synthesis of these studies is needed to support evidence‐based decision making. In 2015, a workshop was convened with researchers, policymakers and industry/business representatives from the UK, EU and internationally. Outcomes from global research on bioenergy land‐use change were compared to identify areas of consensus, key uncertainties, and research priorities. Here, we discuss the strength of evidence for and against six consensus statements summarising the effects of land‐use change to perennial bioenergy crops on the cycling of carbon, nitrogen and water, in the context of the whole life‐cycle of bioenergy production. Our analysis suggests that the direct impacts of dedicated perennial bioenergy crops on soil carbon and nitrous oxide are increasingly well understood and are often consistent with significant life cycle GHG mitigation from bioenergy relative to conventional energy sources. We conclude that the GHG balance of perennial bioenergy crop cultivation will often be favourable, with maximum GHG savings achieved where crops are grown on soils with low carbon stocks and conservative nutrient application, accruing additional environmental benefits such as improved water quality. The analysis reported here demonstrates there is a mature and increasingly comprehensive evidence base on the environmental benefits and risks of bioenergy cultivation which can support the development of a sustainable bioenergy industry.     

High‐resolution spatial modelling of greenhouse gas emissions from land‐use change to energy crops in the United Kingdom

We implemented a spatial application of a previously evaluated model of soil GHG emissions, ECOSSE, in the United Kingdom to examine the impacts to 2050 of land‐use transitions from existing land use, rotational cropland, permanent grassland or woodland, to six bioenergy crops; three ‘first‐generation’ energy crops: oilseed rape, wheat and sugar beet, and three ‘second‐generation’ energy crops: Miscanthus, short rotation coppice willow (SRC) and short rotation forestry poplar (SRF). Conversion of rotational crops to Miscanthus, SRC and SRF and conversion of permanent grass to SRF show beneficial changes in soil GHG balance over a significant area. Conversion of permanent grass to Miscanthus, permanent grass to SRF and forest to SRF shows detrimental changes in soil GHG balance over a significant area. Conversion of permanent grass to wheat, oilseed rape, sugar beet and SRC and all conversions from forest show large detrimental changes in soil GHG balance over most of the United Kingdom, largely due to moving from uncultivated soil to regular cultivation. Differences in net GHG emissions between climate scenarios to 2050 were not significant. Overall, SRF offers the greatest beneficial impact on soil GHG balance. These results provide one criterion for selection of bioenergy crops and do not consider GHG emission increases/decreases resulting from displaced food production, bio‐physical factors (e.g. the energy density of the crop) and socio‐economic factors (e.g. expenditure on harvesting equipment). Given that the soil GHG balance is dominated by change in soil organic carbon (SOC) with the difference among Miscanthus, SRC and SRF largely determined by yield, a target for management of perennial energy crops is to achieve the best possible yield using the most appropriate energy crop and cultivar for the local situation.     

Trade‐offs between land and water requirements for large‐scale bioenergy production

Bioenergy is expected to play an important role in the future energy mix as it can substitute fossil fuels and contribute to climate change mitigation. However, large‐scale bioenergy cultivation may put substantial pressure on land and water resources. While irrigated bioenergy production can reduce the pressure on land due to higher yields, associated irrigation water requirements may lead to degradation of freshwater ecosystems and to conflicts with other potential users. In this article, we investigate the trade‐offs between land and water requirements of large‐scale bioenergy production. To this end, we adopt an exogenous demand trajectory for bioenergy from dedicated energy crops, targeted at limiting greenhouse gas emissions in the energy sector to 1100 Gt carbon dioxide equivalent until 2095. We then use the spatially explicit global land‐ and water‐use allocation model MAgPIE to project the implications of this bioenergy target for global land and water resources. We find that producing 300 EJ yr^?1 of bioenergy in 2095 from dedicated bioenergy crops is likely to double agricultural water withdrawals if no explicit water protection policies are implemented. Since current human water withdrawals are dominated by agriculture and already lead to ecosystem degradation and biodiversity loss, such a doubling will pose a severe threat to freshwater ecosystems. If irrigated bioenergy production is prohibited to prevent negative impacts of bioenergy cultivation on water resources, bioenergy land requirements for meeting a 300 EJ yr^?1 bioenergy target increase substantially (+ 41%) – mainly at the expense of pasture areas and tropical forests. Thus, avoiding negative environmental impacts of large‐scale bioenergy production will require policies that balance associated water and land requirements.     

Is woody bioenergy carbon neutral? A comparative assessment of emissions from consumption of woody bioenergy and fossil fuel

Under the current accounting systems, emissions produced when biomass is burnt for energy are accounted as zero, resulting in what is referred to as the ‘carbon neutrality’ assumption. However, if current harvest levels are increased to produce more bioenergy, carbon that would have been stored in the biosphere might be instead released in the atmosphere. This study utilizes a comparative approach that considers emissions under alternative energy supply options. This approach shows that the emission benefits of bioenergy compared to use of fossil fuel are time‐dependent. It emerges that the assumption that bioenergy always results in zero greenhouse gas (GHG) emissions compared to use of fossil fuels can be misleading, particularly in the context of short‐to‐medium term goals. While it is clear that all sources of woody bioenergy from sustainably managed forests will produce emission reductions in the long term, different woody biomass sources have various impacts in the short‐medium term. The study shows that the use of forest residues that are easily decomposable can produce GHG benefits compared to use of fossil fuels from the beginning of their use and that biomass from dedicated plantations established on marginal land can be carbon neutral from the beginning of its use. However, the risk of short‐to‐medium term negative impacts is high when additional fellings are extracted to produce bioenergy and the proportion of felled biomass used for bioenergy is low, or when land with high C stocks is converted to low productivity bioenergy plantations. The method used in the study provides an instrument to identify the time‐dependent pattern of emission reductions for alternative bioenergy sources. In this way, decision makers can evaluate which bioenergy options are most beneficial for meeting short‐term GHG emission reduction goals and which ones are more appropriate for medium to longer term objectives.     

An agent‐based modelling approach to evaluate factors influencing bioenergy crop adoption in north‐east Scotland

An agent‐based modelling (ABM) framework was adapted to assess bioenergy crop uptake and integrate social and economic processes with biophysical elements. Survey results indicated that economic rationalisation was intrinsic to farmers’ decision‐making, but was not the only consideration. This study presents an approach, set within an established resource management framework, to incorporate a number of key socio‐economic factors, which we call Mitigation Willingness Factors (MWFs), using survey data collected from farmers and land managers, into the ABM. The MWFs represent farmers’ willingness to compromise revenue in order to reduce GHG emissions, derived from their attitudes to climate change and the ability of different economic mechanisms to stimulate energy crop uptake. Adoption of bioenergy crops of different farmer types and farming enterprises was also assessed. Adoption rates and scenarios that take into account noneconomic factors are presented, and particular farming enterprises that may respond more positively to policy initiatives are identified.     

Net land‐atmosphere flows of biogenic carbon related to bioenergy: towards an understanding of systemic feedbacks

The notion that biomass combustion is carbon neutral vis‐a‐vis the atmosphere because carbon released during biomass combustion is absorbed during plant regrowth is inherent in the greenhouse gas accounting rules in many regulations and conventions. But this ‘carbon neutrality’ assumption of bioenergy is an oversimplification that can result in major flaws in emission accounting; it may even result in policies that increase, instead of reduce, overall greenhouse gas emissions. This commentary discusses the systemic feedbacks and ecosystem succession/land‐use history issues ignored by the carbon neutrality assumption. Based on recent literature, three cases are elaborated which show that the C balance of bioenergy may range from highly beneficial to strongly detrimental, depending on the plants grown, the land used (including its land‐use history) as well as the fossil energy replaced. The article concludes by proposing the concept of GHG cost curves of bioenergy as a means for optimizing the climate benefits of bioenergy policies.     

Evaluation of the ECOSSE model for simulating soil organic carbon under Miscanthus and short rotation coppice‐willow crops in Britain

In this paper, we focus on the impact on soil organic carbon (SOC) of two dedicated energy crops: perennial grass Miscanthus x Giganteus (Miscanthus) and short rotation coppice (SRC)‐willow. The amount of SOC sequestered in the soil is a function of site‐specific factors including soil texture, management practices, initial SOC levels and climate; for these reasons, both losses and gains in SOC were observed in previous Miscanthus and SRC‐willow studies. The ECOSSE model was developed to simulate soil C dynamics and greenhouse gas emissions in mineral and organic soils. The performance of ECOSSE has already been tested at site level to simulate the impacts of land‐use change to short rotation forestry (SRF) on SOC. However, it has not been extensively evaluated under other bioenergy plantations, such as Miscanthus and SRC‐willow. Twenty‐nine locations in the United Kingdom, comprising 19 paired transitions to SRC‐willow and 20 paired transitions to Miscanthus, were selected to evaluate the performance of ECOSSE in predicting SOC and SOC change from conventional systems (arable and grassland) to these selected bioenergy crops. The results of the present work revealed a strong correlation between modelled and measured SOC and SOC change after transition to Miscanthus and SRC‐willow plantations, at two soil depths (0–30 and 0–100 cm), as well as the absence of significant bias in the model. Moreover, model error was within (i.e. not significantly larger than) the measurement error. The high degrees of association and coincidence with measured SOC under Miscanthus and SRC‐willow plantations in the United Kingdom, provide confidence in using this process‐based model for quantitatively predicting the impacts of future land use on SOC, at site level as well as at national level.     

Towards an integrated global framework to assess the impacts of land use and management change on soil carbon: current capability and future vision

Intergovernmental Panel on Climate Change (IPCC) Tier 1 methodologies commonly underpin project‐scale carbon accounting for changes in land use and management and are used in frameworks for Life Cycle Assessment and carbon footprinting of food and energy crops. These methodologies were intended for use at large spatial scales. This can introduce error in predictions at finer spatial scales. There is an urgent need for development and implementation of higher tier methodologies that can be applied at fine spatial scales (e.g. farm/project/plantation) for food and bioenergy crop greenhouse gas (GHG) accounting to facilitate decision making in the land‐based sectors. Higher tier methods have been defined by IPCC and must be well evaluated and operate across a range of domains (e.g. climate region, soil type, crop type, topography), and must account for land use transitions and management changes being implemented. Furthermore, the data required to calibrate and drive the models used at higher tiers need to be available and applicable at fine spatial resolution, covering the meteorological, soil, cropping system and management domains, with quantified uncertainties. Testing the reliability of the models will require data either from sites with repeated measurements or from chronosequences. We review current global capability for estimating changes in soil carbon at fine spatial scales and present a vision for a framework capable of quantifying land use change and management impacts on soil carbon, which could be used for addressing issues such as bioenergy and biofuel sustainability, food security, forest protection, and direct/indirect impacts of land use change. The aim of this framework is to provide a globally accepted standard of carbon measurement and modelling appropriate for GHG accounting that could be applied at project to national scales (allowing outputs to be scaled up to a country level), to address the impacts of land use and land management change on soil carbon.     

A realistic meteorological assessment of perennial biofuel crop deployment: a Southern Great Plains perspective

Utility of perennial bioenergy crops (e.g., switchgrass and miscanthus) offers unique opportunities to transition toward a more sustainable energy pathway due to their reduced carbon footprint, averted competition with food crops, and ability to grow on abandoned and degraded farmlands. Studies that have examined biogeophysical impacts of these crops noted a positive feedback between near‐surface cooling and enhanced evapotranspiration (ET), but also potential unintended consequences of soil moisture and groundwater depletion. To better understand hydrometeorological effects of perennial bioenergy crop expansion, this study conducted high‐resolution (2‐km grid spacing) simulations with a state‐of‐the‐art atmospheric model (Weather Research and Forecasting system) dynamically coupled to a land surface model. We applied the modeling system over the Southern Plains of the United States during a normal precipitation year (2007) and a drought year (2011). By focusing the deployment of bioenergy cropping systems on marginal and abandoned farmland areas (to reduce the potential conflict with food systems), the research presented here is the first realistic examination of hydrometeorological impacts associated with perennial bioenergy crop expansion. Our results illustrate that the deployment of perennial bioenergy crops leads to widespread cooling (1–2 °C) that is largely driven by an enhanced reflection of shortwave radiation and, secondarily, due to an enhanced ET. Bioenergy crop deployment was shown to reduce the impacts of drought through simultaneous moistening and cooling of the near‐surface environment. However, simulated impacts on near‐surface cooling and ET were reduced during the drought relative to a normal precipitation year, revealing differential effects based on background environmental conditions. This study serves as a key step toward the assessment of hydroclimatic sustainability associated with perennial bioenergy crop expansion under diverse hydrometeorological conditions by highlighting the driving mechanisms and processes associated with this energy pathway.     

Atmospheric impact of bioenergy based on perennial crop (reed canary grass,Phalaris arundinaceae,L.) cultivation on a drained boreal organic soil

Marginal organic soils, abundant in the boreal region, are being increasingly used for bioenergy crop cultivation. Using long‐term field experimental data on greenhouse gas (GHG) balance from a perennial bioenergy crop [reed canary grass (RCG), Phalaris arundinaceae L.] cultivated on a drained organic soil as an example, we show here for the first time that, with a proper cultivation and land‐use practice, environmentally sound bioenergy production is possible on these problematic soil types. We performed a life cycle assessment (LCA) for RCG on this organic soil. We found that, on an average, this system produces 40% less CO₂‐equivalents per MWh of energy in comparison with a conventional energy source such as coal. Climatic conditions regulating the RCG carbon exchange processes have a high impact on the benefits from this bioenergy production system. Under appropriate hydrological conditions, this system can even be carbon‐negative. An LCA sensitivity analysis revealed that net ecosystem CO₂ exchange and crop yield are the major LCA components, while non‐CO₂ GHG emissions and costs associated with crop production are the minor ones. Net bioenergy GHG emissions resulting from restricted net CO₂ uptake and low crop yields, due to climatic and moisture stress during dry years, were comparable with coal emissions. However, net bioenergy emissions during wet years with high net uptake and crop yield were only a third of the coal emissions. As long‐term experimental data on GHG balance of bioenergy production are scarce, scientific data stemming from field experiments are needed in shaping renewable energy source policies.     

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.     

Evaluation of the ECOSSE model for simulating soil carbon under short rotation forestry energy crops in Britain

Understanding and predicting the effects of land‐use change to short rotation forestry (SRF) on soil carbon (C) is an important requirement for fully assessing the C mitigation potential of SRF as a bioenergy crop. There is little current knowledge of SRF in the UK and in particular a lack of consistent measured data sets on the direct impacts of land use change on soil C stocks. The ECOSSE model was developed to simulate soil C dynamics and greenhouse gas (GHG) emissions in mineral and organic soils. The ECOSSE model has already been applied spatially to simulate land‐use change impacts on soil C and GHG emissions. However, it has not been extensively evaluated under SRF. Eleven sites comprising 29 transitions in Britain, representing land‐use change from nonwoodland land uses to SRF, were selected to evaluate the performance of ECOSSE in predicting soil C and soil C change in SRF plantations. The modelled C under SRF showed a strong correlation with the soil C measurements at both 0–30 cm (R = 0.93) and 0–100 cm soil depth (R = 0.82). As for the SRF plots, the soil C at the reference sites have been accurately simulated by the model. The extremely high correlation for the reference fields (R ≥ 0.99) shows a good performance of the model spin‐up. The statistical analysis of the model performance to simulate soil C and soil C changes after land‐use change to SRF highlighted the absence of significant error between modelled and measured values as well as the absence of significant bias in the model. Overall, this evaluation reinforces previous studies on the ability of ECOSSE to simulate soil C and emphasize its accuracy to simulate soil C under SRF plantations.     

21st‐century biogeochemical modeling: Challenges for Century‐based models and where do we go from here?

21st‐century modeling of greenhouse gas (GHG) emissions from bioenergy crops is necessary to quantify the extent to which bioenergy production can mitigate climate change. For over 30 years, the Century‐based biogeochemical models have provided the preeminent framework for belowground carbon and nitrogen cycling in ecosystem and earth system models. While monthly Century and the daily time‐step version of Century (DayCent) have advanced our ability to predict the sustainability of bioenergy crop production, new advances in feedstock generation, and our empirical understanding of sources and sinks of GHGs in soils call for a re‐visitation of DayCent's core model structures. Here, we evaluate current challenges with modeling soil carbon dynamics, trace gas fluxes, and drought and age‐related impacts on bioenergy crop productivity. We propose coupling a microbial process‐based soil organic carbon and nitrogen model with DayCent to improve soil carbon dynamics. We describe recent improvements to DayCent for simulating unique plant structural and physiological attributes of perennial bioenergy grasses. Finally, we propose a method for using machine learning to identify key parameters for simulating N₂O emissions. Our efforts are focused on meeting the needs for modeling bioenergy crops; however, many updates reviewed and suggested to DayCent will be broadly applicable to other systems.     

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.     

Greenhouse gas emissions from four bioenergy crops in England and Wales: Integrating spatial estimates of yield and soil carbon balance in life cycle analyses

Accurate estimation of the greenhouse gas (GHG) mitigation potential of bioenergy crops requires the integration of a significant component of spatially varying information. In particular, crop yield and soil carbon (C) stocks are variables which are generally soil type and climate dependent. Since gaseous emissions from soil C depend on current C stocks, which in turn are related to previous land management it is important to consider both previous and proposed future land use in any C accounting assessment. We have conducted a spatially explicit study for England and Wales, coupling empirical yield maps with the RothC soil C turnover model to simulate soil C dynamics. We estimate soil C changes under proposed planting of four bioenergy crops, Miscanthus ( Miscanthus × giganteus ), short rotation coppice (SRC) poplar ( Populus trichocarpa Torr. & Gray × P. trichocarpa , var. Trichobel), winter wheat, and oilseed rape. This is then related to the former land use – arable, pasture, or forest/seminatural, and the outputs are then assessed in the context of a life cycle analysis (LCA) for each crop. By offsetting emissions from management under the previous land use, and considering fossil fuel C displaced, the GHG balance is estimated for each of the 12 land use change transitions associated with replacing arable, grassland, or forest/seminatural land, with each of the four bioenergy crops. Miscanthus and SRC are likely to have a mostly beneficial impact in reducing GHG emissions, while oilseed rape and winter wheat have either a net GHG cost, or only a marginal benefit. Previous land use is important and can make the difference between the bioenergy crop being beneficial or worse than the existing land use in terms of GHG balance.     

Subnational greenhouse gas and land‐based biodiversity footprints in the European Union

Insights into subnational environmental impacts and the underlying drivers are scarce, especially from a consumption‐based perspective. Here, we quantified greenhouse gas (GHG) emissions and land‐based biodiversity losses associated with final consumption in 162 regions in the European Union in 2010. For this purpose, we developed an environmentally extended multi‐regional input–output (MRIO) model with subnational European information on demand, production, and trade structures subdivided into 18 major economic sectors, while accounting for trade outside Europe. We employed subnational data on land use and national data on GHG emissions. Our results revealed within‐country differences in per capita GHG and land‐based biodiversity footprints up to factors of 3.0 and 3.5, respectively, indicating that national footprints may mask considerable subnational variability. The per capita GHG footprint increased with per capita income and income equality, whereas we did not find such responses for the per capita land‐based biodiversity footprint, reflecting that extra income is primarily spent on energy‐intensive activities. Yet, we found a shift from the domestic to the foreign part of the biodiversity footprints with rising population density and income. Because our analysis showed that most regions are already net importers of GHG emissions and biodiversity losses, we conclude that it is increasingly important to address the role of trade in national and regional policies on mitigating GHG emissions and averting further biodiversity losses, both within and outside the region itself. To further increase the policy relevance of subnational footprint analyses, we also recommend the compilation of more detailed subnational MRIO databases including harmonized environmental data.     

Global simulation of bioenergy crop productivity: analytical framework and case study for switchgrass

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global‐scale agro‐ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field‐trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high‐performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC‐Environmental Policy Integrated Climate (HPC‐EPIC) model simulated a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field‐trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.     

Plant roots and GHG mitigation in native perennial bioenergy cropping systems

Native perennial bioenergy crops can mitigate greenhouse gases (GHG) by displacing fossil fuels with renewable energy and sequestering atmospheric carbon (C) in soil and roots. The relative contribution of root C to net GHG mitigation potential has not been compared in perennial bioenergy crops ranging in species diversity and N fertility. We measured root biomass, C, nitrogen (N), and soil organic carbon (SOC) in the upper 90 cm of soil for five native perennial bioenergy crops managed with and without N fertilizer. Bioenergy crops ranged in species composition and were annually harvested for 6 (one location) and 7 years (three locations) following the seeding year. Total root biomass was 84% greater in switchgrass (Panicum virgatum L.) and a four‐species grass polyculture compared to high‐diversity polycultures; the difference was driven by more biomass at shallow soil depth (0–30 cm). Total root C (0–90 cm) ranged from 3.7 Mg C ha^?1 for a 12‐species mixture to 7.6 Mg C ha^?1 for switchgrass. On average, standing root C accounted for 41% of net GHG mitigation potential. After accounting for farm and ethanol production emissions, net GHG mitigation potential from fossil fuel offsets and root C was greatest for switchgrass (?8.4 Mg CO2e ha^?1 yr^?1) and lowest for high‐diversity mixtures (?4.5 Mg CO2e ha^?1 yr^?1). Nitrogen fertilizer did not affect net GHG mitigation potential or the contribution of roots to GHG mitigation for any bioenergy crop. SOC did not change and therefore did not contribute to GHG mitigation potential. However, associations among SOC, root biomass, and root C : N ratio suggest greater long‐term C storage in diverse polycultures vs. switchgrass. Carbon pools in roots have a greater effect on net GHG mitigation than SOC in the short‐term, yet variation in root characteristics may alter patterns in long‐term C storage among bioenergy crops.     

LCA of energetic biomass utilization: actual projects and new developments—April 23, 2012, Berne, Switzerland

Introduction

In the last years, the use of biomass for energy purposes has been seen as a promising option to reduce the use of nonrenewable energy sources and the emissions of fossil carbon. However, LCA studies have shown that the energetic use of biomass also causes impacts on climate change and, furthermore, that different environmental issues arise, such as land use and agricultural emissions. While biomass is renewable, it is not an unlimited resource. Its use, to whatever purpose, must therefore be well studied to promote the most efficient option with the least environmental impacts. The 47th LCA Discussion Forum gathered several national and international speakers who provided a broad and qualified view on the topic.

Summary of the topics presented in DF 47

Several aspects of energetic biomass use from a range of projects financed by the Swiss Federal Office of Energy (SFOE) were presented in this Discussion Forum. The first session focused on important aspects of the agricultural biogas production like the use of high energy crops or catch crops as well as the influence of plant size on the environmental performance of biogas. In the second session, other possibilities of biomass treatment like direct combustion, composting, and incineration with municipal waste were presented. Topic of the first afternoon session was the update and harmonization of biomass inventories and the resulting new assessment of biofuels. The short presentations investigated some further aspects of the LCA of bioenergy like the assessment of spatial variation of greenhouse gas (GHG) emissions from bioenergy production in a country, the importance of indirect land use change emissions on the overall results, the assessment of alternative technologies to direct spreading of digestate or the updates of the car operation datasets in ecoinvent.

Conclusions

One main outcome of this Discussion Forum is that bioenergy is not environmentally friendly per se. In many cases, energetic use of biomass allows a reduction of GHG and fossil energy use. However, there is often a tradeoff with other environmental impacts linked to agricultural production like eutrophication or ecotoxicity. Methodological challenges still exist, like the assessment of direct and indirect land use change emissions and their attribution to the bioenergy production, or the influence of heavy metal flows on the bioenergy assessment. Another challenge is the implementation of a life cycle approach in certification or legislation schemes, as shown by the example of the Renewable Energy Directive of the European Union.     

Estimating product and energy substitution benefits in national‐scale mitigation analyses for Canada

The potential of forests and the forest sector to mitigate greenhouse gas (GHG) emissions is widely recognized, but challenging to quantify at a national scale. Mitigation benefits through the use of forest products are affected by product life cycles, which determine the duration of carbon storage in wood products and substitution benefits where emissions are avoided using wood products instead of other emissions‐intensive building products and energy fuels. Here we determined displacement factors for wood substitution in the built environment and bioenergy at the national level in Canada. For solid wood products, we compiled a basket of end‐use products and determined the reduction in emissions for two functionally equivalent products: a more wood‐intensive product vs. a less wood‐intensive one. Avoided emissions for end‐use products basket were weighted by Canadian consumption statistics to reflect national wood uses, and avoided emissions were further partitioned into displacement factors for sawnwood and panels. We also examined two bioenergy feedstock scenarios (constant supply and constrained supply) to estimate displacement factors for bioenergy using an optimized selection of bioenergy facilities which maximized avoided emissions from fossil fuels. Results demonstrated that the average displacement factors were found to be similar: product displacement factors were 0.54 tC displaced per tC of used for sawnwood and 0.45 tC tC^?1 for panels; energy displacement factors for the two feedstock scenarios were 0.47 tC tC^?1 for the constant supply and 0.89 tC tC^?1 for the constrained supply. However, there was a wide range of substitution impacts. The greatest avoided emissions occurred when wood was substituted for steel and concrete in buildings, and when bioenergy from heat facilities and/or combined heat and power facilities was substituted for energy from high‐emissions fossil fuels. We conclude that (1) national‐level substitution benefits need to be considered within a systems perspective on climate change mitigation to avoid the development of policies that deliver no net benefits to the atmosphere, (2) the use of long‐lived wood products in buildings to displace steel and concrete reduces GHG emissions, (3) the greatest bioenergy substitution benefits are achieved using a mix of facility types and capacities to displace emissions‐intensive fossil fuels.