A new hybrid method for reducing the gap between WTW and LCA in the carbon footprint assessment of electric vehicles

Purpose

The well-to-wheel (WTW) methodology is widely used for policy support in road transport. It can be seen as a simplified life cycle assessment (LCA) that focuses on the energy consumption and CO₂ emissions only for the fuel being consumed, ignoring other stages of a vehicle’s life cycle. WTW results are therefore different from LCA results. In order to close this gap, the authors propose a hybrid WTW+LCA methodology useful to assess the greenhouse gas (GHG) profiles of road vehicles.

Methods

The proposed method (hybrid WTW+LCA) keeps the main hypotheses of the WTW methodology, but integrates them with LCA data restricted to the global warming potential (GWP) occurring during the manufacturing of the battery pack. WTW data are used for the GHG intensity of the EU electric mix, after a consistency check with the main life cycle impact (LCI) sources available in literature.

Results and discussion

A numerical example is provided, comparing GHG emissions due to the use of a battery electric vehicle (BEV) with emissions from an internal combustion engine vehicle. This comparison is done both according to the WTW approach (namely the JEC WTW version 4) and the proposed hybrid WTW+LCA method. The GHG savings due to the use of BEVs calculated with the WTW-4 range between 44 and 56 %, while according to the hybrid method the savings are lower (31–46 %). This difference is due to the GWP which arises as a result of the manufacturing of the battery pack for the electric vehicles.

Conclusions

The WTW methodology used in policy support to quantify energy content and GHG emissions of fuels and powertrains can produce results closer to the LCA methodology by adopting a hybrid WTW+LCA approach. While evaluating GHG savings due to the use of BEVs, it is important that this method considers the GWP due to the manufacturing of the battery pack.

     

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products—a case study on laundry washing in Europe

Purpose

Variability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.

Methods

Data from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.

Results and discussion

Both inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5?×?10² g CO_2?eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.

Conclusions

The combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

     

产业园区温室气体排放清单

温室气体排放所导致的全球气候变化是国际社会长期关注的热点问题,它严重限制了人类社会的发展并威胁着人类的生存。产业园区通常集中了一个区域主要的生产要素与生产能力,也代表着特定产业在该区域的发展水平,理应作为发展低碳经济的基础单元和减少温室气体排放的重要控制点,也可以成为解决区域资源、环境问题的突破口。明确了产业园区温室气体排放的系统边界和内部结构,梳理了产业园区全生命周期温室气体排放行为,综合考虑产业园区能源消耗、工业生产、物质材料消耗、仪器设备投入、废弃物处理处置、景观绿化等过程,建立产业园区温室气体排放核算方法,并对案例园区进行了清单分析。结果表明:案例园区整个生命周期的温室气体排放量为1872177 t CO2-eq,其中运行管理阶段占全生命周期排放的比例最高,为95.35%。建设阶段的温室气体排放总量中建筑材料消耗引起的排放占到96.95%,主要集中在建筑工程、内部装修工程和外部装饰工程3个环节。运行管理阶段电力消耗、热力消耗和污水处理过程的排放量占到总量的98.69%。根据核算及分析结果提出了案例园区在建设和运行管理阶段实现温室气体减排的建议。     

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.     

Balancing conservation and climate change – a methodology using existing data demonstrated for twelve UK priority habitats

Mitigation of climate change (CC) is a regulating ecosystem service provided by priority habitats that is often co-delivered alongside their conservation of biodiversity. Carefully planned conservation management is thought necessary to support biodiversity adaptation to CC, but could also contribute to CC mitigation. This paper presents a methodology for assessing direct emissions of greenhouse gases (GHG: CO₂, CH₄ and N₂O) from 12 UK priority habitats in 26 Special Areas of Conservation (SAC) using readily available data. Background emissions are estimated on the basis of published field research. The contribution of conservation management to GHG emission reduction is estimated using the IPCC GHG accounting methodology and other methods. Management Data Acquisition surveys carried out at selected SACs provided data on management practises for Scotland and Wales. Climate change mitigation actions identified in this study for priority habitats included livestock removal or change in stocking density, with GHG reduction potential of up to 3 tCO₂e/animal/year, afforestation of acid grasslands—up to 19.4 tCO₂e/ha/year, wetland restoration—0.3–0.8 tCO₂e/ha/year and cessation of moorland burning—6.9 tCO₂e/ha/year. Estimated GHG emissions from priority habitats can be used to identify win:win management options that co-deliver GHG mitigation, climate adaptation and conservation benefits for consideration by policy makers and conservation managers.     

Bioethanol production from sugarcane and emissions of greenhouse gases – known and unknowns

Bioethanol production from sugarcane is discussed as an alternative energy source to reduce dependencies of regional economies on fossil fuels. Even though bioethanol production from sugarcane is considered to be a beneficial and cost‐effective greenhouse gas (GHG) mitigation strategy, it is still a matter of controversy due to insufficient information on the total GHG balance of this system. Aside from the necessity to account for the impact of land use change (LUC), soil N₂O emissions during sugarcane production and emissions of GHG due to preharvest burning may significantly impact the GHG balance. Based on a thorough literature review, we show that direct N₂O emissions from sugarcane fields due to nitrogen (N) fertilization result in an emission factor of 3.87±1.16% which is much higher than suggested by IPCC (1%). N₂O emissions from N fertilization accounted for 40% of the total GHG emissions from ethanol–sugarcane production, with an additional 17% from trash burning. If LUC‐related GHG emissions are considered, the total GHG balance turns negative mainly due to vegetation carbon losses. Our study also shows that major gaps in knowledge still exist about GHG sources related to agricultural management during sugarcane production, e.g. effects of irrigation, vinasse and filter cake application. Therefore, more studies are needed to assess if bioethanol from sugarcane is a viable option to reduce energy‐related GHG emissions.     

Contribution of Urban Water Supply to Greenhouse Gas Emissions in China

Greenhouse gas (GHG) emissions from energy use in the water sector in China have not received the same attention as emissions from other sectors, but interest in this area is growing. This study uses 2011 data to investigate GHG emissions from electricity use for urban water supply in China. The objective is to measure the climate cobenefit of water conservation, compare China with other areas on a number of emissions indicators, and assist in development of policy that promotes low‐emission water supply. Per capita and per unit GHG emissions for water supplied to urban areas in China in 2011 were 24.5 kilograms carbon dioxide equivalent (kg CO₂‐eq) per capita per year and 0.213 kg CO₂‐eq per cubic meter, respectively. Comparison of provinces within China revealed that GHG emissions for urban water supply as a percentage of total province‐wide emissions from electricity use correlate directly with the rate of leakage and water loss within the water distribution system. This highlights controlling leakage as a possible means of reducing the contribution of urban water supply to GHG emissions. An inverse correlation was established between GHG emissions per unit water and average per capita daily water use, which implies that water demand tends to be higher when per unit emissions are lower. China's high emission factor for electricity generation inflates emissions for urban water supply. Shifting from emissions‐intensive electricity sources is crucial to reducing emissions in the water supply sector.     

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.     

The Environmental Foodprint of Obesity

Emissions of greenhouse gases (GHG) are linked to global warming and adverse climate changes. Meeting the needs of the increasing number of people on the planet presents a challenge for reducing total GHG burden. A further challenge may be the size of the average person on the planet and the increasing number of people with excess body weight. We used data on GHG emissions from various sources and estimated that obesity is associated with ~20% greater GHG emissions compared with the normal‐weight state. On a global scale, obesity contributes to an extra GHG emissions of ~49 megatons per year of CO₂ equivalent (CO₂eq) from oxidative metabolism due to greater metabolic demands, ~361 megatons per year of CO₂eq from food production processes due to increased food intake, and ~290 megatons per year of CO₂eq from automobile and air transportation due to greater body weight. Therefore, the total impact of obesity may be extra emissions of ~700 megatons per year of CO₂eq, which is about 1.6% of worldwide GHG emissions. Inasmuch as obesity is an important contributor to global GHG burden, strategies to reduce its prevalence should prioritize efforts to reduce GHG emissions. Accordingly, reducing obesity may have considerable benefits for both public health and the environment.     

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.

     

Mitigation of ammonia,nitrous oxide and methane emissions from manure management chains: a meta‐analysis and integrated assessment

Livestock manure contributes considerably to global emissions of ammonia (NH₃) and greenhouse gases (GHG), especially methane (CH₄) and nitrous oxide (N₂O). Various measures have been developed to mitigate these emissions, but most of these focus on one specific gas and/or emission source. Here, we present a meta‐analysis and integrated assessment of the effects of mitigation measures on NH₃, CH₄ and (direct and indirect) N₂O emissions from the whole manure management chain. We analysed the effects of mitigation technologies on NH₃, CH₄ and N₂O emissions from individual sources statistically using results of 126 published studies. Whole‐chain effects on NH₃ and GHG emissions were assessed through scenario analysis. Significant NH₃ reduction efficiencies were observed for (i) housing via lowering the dietary crude protein (CP) content (24–65%, compared to the reference situation), for (ii) external slurry storages via acidification (83%) and covers of straw (78%) or artificial films (98%), for (iii) solid manure storages via compaction and covering (61%, compared to composting), and for (iv) manure application through band spreading (55%, compared to surface application), incorporation (70%) and injection (80%). Acidification decreased CH₄ emissions from stored slurry by 87%. Significant increases in N₂O emissions were found for straw‐covered slurry storages (by two orders of magnitude) and manure injection (by 26–199%). These side‐effects of straw covers and slurry injection on N₂O emission were relatively small when considering the total GHG emissions from the manure chain. Lowering the CP content of feed and acidifying slurry are strategies that consistently reduce NH₃ and GHG emissions in the whole chain. Other strategies may reduce emissions of a specific gas or emissions source, by which there is a risk of unwanted trade‐offs in the manure management chain. Proper farm‐scale combinations of mitigation measures are important to minimize impacts of livestock production on global emissions of NH₃ and GHG.     

Decoupling of greenhouse gas emissions from global agricultural production: 1970–2050

Since 1970 global agricultural production has more than doubled; contributing ~1/4 of total anthropogenic greenhouse gas (GHG) burden in 2010. Food production must increase to feed our growing demands, but to address climate change, GHG emissions must decrease. Using an identity approach, we estimate and analyse past trends in GHG emission intensities from global agricultural production and land‐use change and project potential future emissions. The novel Kaya–Porter identity framework deconstructs the entity of emissions from a mix of multiple sources of GHGs into attributable elements allowing not only a combined analysis of the total level of all emissions jointly with emissions per unit area and emissions per unit product. It also allows us to examine how a change in emissions from a given source contributes to the change in total emissions over time. We show that agricultural production and GHGs have been steadily decoupled over recent decades. Emissions peaked in 1991 at ~12 Pg CO₂‐eq. yr^?1 and have not exceeded this since. Since 1970 GHG emissions per unit product have declined by 39% and 44% for crop‐ and livestock‐production, respectively. Except for the energy‐use component of farming, emissions from all sources have increased less than agricultural production. Our projected business‐as‐usual range suggests that emissions may be further decoupled by 20–55% giving absolute agricultural emissions of 8.2–14.5 Pg CO₂‐eq. yr^?1 by 2050, significantly lower than many previous estimates that do not allow for decoupling. Beyond this, several additional costcompetitive mitigation measures could reduce emissions further. However, agricultural GHG emissions can only be reduced to a certain level and a simultaneous focus on other parts of the food‐system is necessary to increase food security whilst reducing emissions. The identity approach presented here could be used as a methodological framework for more holistic food systems analysis.     

Contribution of litter layer to soil greenhouse gas emissions in a temperate beech forest

Background and aims

The litter layer is a major source of CO₂, and it also influences soil-atmosphere exchange of N₂O and CH₄. So far, it is not clear how much of soil greenhouse gas (GHG) emission derives from the litter layer itself or is litter-induced. The present study investigates how the litter layer controls soil GHG fluxes and microbial decomposer communities in a temperate beech forest.

Methods

We removed the litter layer in an Austrian beech forest and studied responses of soil CO₂, CH₄ and N₂O fluxes and the microbial community via phospholipid fatty acids (PLFA). Soil GHG fluxes were determined with static chambers on 22 occasions from July 2012 to February 2013, and soil samples collected at 8 sampling events.

Results

Litter removal reduced CO₂ emissions by 30 % and increased temperature sensitivity (Q₁₀) of CO₂ fluxes. Diffusion of CH₄ into soil was facilitated by litter removal and CH₄ uptake increased by 16 %. This effect was strongest in autumn and winter when soil moisture was high. Soils without litter turned from net N₂O sources to slight N₂O sinks because N₂O emissions peaked after rain events in summer and autumn, which was not the case in litter-removal plots. Microbial composition was only transiently affected by litter removal but strongly influenced by seasonality.

Conclusions

Litter layers must be considered in calculating forest GHG budgets, and their influence on temperature sensitivity of soil GHG fluxes taken into account for future climate scenarios.

     

Which cropland greenhouse gas mitigation options give the greatest benefits in different world regions? Climate and soil‐specific predictions from integrated empirical models

Major sources of greenhouse gas (GHG) emissions from agricultural crop production are nitrous oxide (N₂O) emissions resulting from the application of mineral and organic fertilizer, and carbon dioxide (CO₂) emissions from soil carbon losses. Consequently, choice of fertilizer type, optimizing fertilizer application rates and timing, reducing microbial denitrification and improving soil carbon management are focus areas for mitigation. We have integrated separate models derived from global data on fertilizer‐induced soil N₂O emissions, soil nitrification inhibitors, and the effects of tillage and soil inputs of soil C stocks into a single model to determine optimal mitigation options as a function of soil type, climate, and fertilization rates. After Monte Carlo sampling of input variables, we aggregated the outputs according to climate, soil and fertilizer factors to consider the benefits of several possible emissions mitigation strategies, and identified the most beneficial option for each factor class on a per‐hectare basis. The optimal mitigation for each soil‐climate‐region was then mapped to propose geographically specific optimal GHG mitigation strategies for crops with varying N requirements. The use of empirical models reduces the requirements for validation (as they are calibrated on globally or continentally observed phenomena). However, as they are relatively simple in structure, they may not be applicable for accurate site‐specific prediction of GHG emissions. The value of this modelling approach is for initial screening and ranking of potential agricultural mitigation options and to explore the potential impact of regional agricultural GHG abatement policies. Given the clear association between management practice and crop productivity, it is essential to incorporate characterization of the yield effect on a given crop before recommending any mitigation practice.     

Improving the integrated hybrid LCA in the upstream scope 3 emissions inventory analysis

Purpose

The protocols of carbon footprints generally define three scopes for different greenhouse gas (GHG) emissions levels. The most important carbon footprint emissions source comes from upstream indirect emissions of scope 3 for products that do not consume energy during their use phase. Upstream scope 3 GHG inventory can usually be analyzed through input–output or hybrid LCA analysis. The economic input–output life cycle analysis (EIO-LCA) and the hybrid LCA model have been widely used for this purpose. However, a cutoff error exists in the hybrid model, and the lack of a truncation criterion between process and IO inventory may lead to a high level of uncertainty in the hybrid model. This study attempts to improve the problem of cutoff uncertainty in hybrid LCA and proposes a method to minimize the cutoff uncertainty.

Methods

The way to improve the cutoff uncertainty could follow two steps. First, through the IO inventory analysis of EIO-LCA, we can define the emissions by various tiers of product components. The IO inventory indicator can provide a definitive criterion for the process inventory of the hybrid model. Second, we connect the process- and IO-LCI according to the IO inventory result. The advantage of the process inventory is that it provides detailed manufacturing information on the target while the IO encompasses a complete system boundary. For improvements, the process inventory can catch the most important process of the GHG emissions, and the IO inventory could compensate for the remainder of the incomplete system inventory.

Results and discussion

In this case study, the printed circuit board production process is used to evaluate the efficiency of the improved method. The threshold M was set to 70 in this case study, and the IO inventory provides the remaining 30 %. For the integrated hybrid model, the tier 3 process inventory takes only 64 % while the incorporation of the proposed method can include 92 % of the total emissions, which shows the cutoff uncertainty can be reduced through the improvement.

Conclusions

This study provides a clear guideline for process and IO cutoff criteria, which can help the truncation uncertainty. When higher precision is required, process LCI will need to play an important role, and thus, a higher M value should be set. In this situation, the emissions from IO-LCI would be smaller than the emissions from the process LCI. The appropriate solution would attain a comfortable balance between data accuracy and time and labor consumption.     

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.     

Function and limits of biofilters for the removal of methane in exhaust gases from the pig industry

The agricultural sector is responsible for an important part of Canadian greenhouse gas (GHG) emissions, 8 % of the 747 Mt eq. CO₂ emitted each year. The pork industry, a key sector of the agrifood industry, has had a rapid growth in Canada since the middle 1980s. For this industry, slurry storage accounts for the major part of methane (CH₄) emissions, a GHG 25 times higher than carbon dioxide (CO₂) on a 100-year time horizon. Intending to reduce these emissions, biofiltration, a process effective to treat CH₄ from landfills and coal mines, could be effective to treat CH₄ from the pig industry. Biofiltration is a complex process that requires the understanding of the biological process of CH₄ oxidation and a control of the engineering parameters (filter bed, temperature, etc.). Some biofiltration studies show that this technology could be used to treat CH₄ at a relatively low cost and with a relatively high purification performance.     

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.     

High emissions of greenhouse gases from grasslands on peat and other organic soils

Drainage has turned peatlands from a carbon sink into one of the world's largest greenhouse gas (GHG) sources from cultivated soils. We analyzed a unique data set (12 peatlands, 48 sites and 122 annual budgets) of mainly unpublished GHG emissions from grasslands on bog and fen peat as well as other soils rich in soil organic carbon (SOC) in Germany. Emissions and environmental variables were measured with identical methods. Site‐averaged GHG budgets were surprisingly variable (29.2 ± 17.4 t CO₂‐eq. ha^?1 yr^?1) and partially higher than all published data and the IPCC default emission factors for GHG inventories. Generally, CO₂ (27.7 ± 17.3 t CO₂ ha^?1 yr^?1) dominated the GHG budget. Nitrous oxide (2.3 ± 2.4 kg N₂O‐N ha^?1 yr^?1) and methane emissions (30.8 ± 69.8 kg CH₄‐C ha^?1 yr^?1) were lower than expected except for CH₄ emissions from nutrient‐poor acidic sites. At single peatlands, CO₂ emissions clearly increased with deeper mean water table depth (WTD), but there was no general dependency of CO₂ on WTD for the complete data set. Thus, regionalization of CO₂ emissions by WTD only will remain uncertain. WTD dynamics explained some of the differences between peatlands as sites which became very dry during summer showed lower emissions. We introduced the aerated nitrogen stock (N_air) as a variable combining soil nitrogen stocks with WTD. CO₂ increased with N_air across peatlands. Soils with comparatively low SOC concentrations showed as high CO₂ emissions as true peat soils because N_air was similar. N₂O emissions were controlled by the WTD dynamics and the nitrogen content of the topsoil. CH₄ emissions can be well described by WTD and ponding duration during summer. Our results can help both to improve GHG emission reporting and to prioritize and plan emission reduction measures for peat and similar soils at different scales.     

Carbon footprint of a Cavendish banana supply chain

Purpose

Bananas are one of the highest selling fruits worldwide, and for several countries, bananas are an important export commodity. However, very little is known about banana’s contribution to global warming. The aims of this work were to study the greenhouse gas emissions of bananas from cradle to retail and cradle to grave and to assess the potential of reducing greenhouse gas (GHG) emissions along the value chain.

Methods

Carbon footprint methodology based on ISO-DIS 14067 was used to assess GHG emissions from 1 kg of bananas produced at two plantations in Costa Rica including transport by cargo ship to Norway. Several methodological issues are not clearly addressed in ISO 14067 or the LCA standards 14040 and ISO 14044 underpinning 14067. Examples are allocation, allocation in recycling, representativity and system borders. Methodological choices in this study have been made based on other standards, such as the GHG Protocol Products Standard.

Results and discussion

The results indicate that bananas had a carbon footprint (CF) on the same level as other tropical fruits and that the contribution from the primary production stage was low. However, the methodology used in this study and the other comparative studies was not necessarily identical; hence, no definitive conclusions can be drawn. Overseas transport and primary production were the main contributors to the total GHG emissions. Including the consumer stage resulted in a 34 % rise in CF, mainly due to high wastage. The main potential reductions of GHG emissions were identified at the primary production, within the overseas transport stage and at the consumer.

Conclusions

The carbon footprint of bananas from cradle to retail was 1.37 kg CO₂ per kilogram banana. GHG emissions from transport and primary production could be significantly reduced, which could theoretically give a reduction of as much as 44 % of the total cradle-to-retail CF. The methodology was important for the end result. The choice of system boundaries gives very different results depending on which life cycle stages and which unit processes are included. Allocation issues were also important, both in recycling and in other processes such as transport and storage. The main uncertainties of the CF result are connected to N₂O emissions from agriculture, methane emissions from landfills, use of secondary data and variability in the primary production data. Thus, there is a need for an internationally agreed calculation method for bananas and other food products if CFs are to be used for comparative purposes.