Effect of geographical location and stochastic weather variation on life cycle assessment of biodiesel production from camelina in the northwestern USA

Purpose

The effect of regional factors on life cycle assessment (LCA) of camelina seed production and camelina methyl ester production was assessed in this study. While general conclusions from LCA studies point to lower environmental impacts of biofuels, it has been shown in many studies that the environmental impacts are dependent on location, production practices, and even local weather variations.

Methods

A cradle-to-farm gate and well-to-pump approaches were used to conduct the LCA. To demonstrate the impact of agro-climatic and management factors (weather condition, soil characteristics, and management practices) on the overall emissions for four different regions including Corvallis, OR, Pendleton, OR, Pullman, WA, and Sheridan, WY, field emissions were simulated using the DeNitrification-DeComposition (DNDC) model. openLCA v.1.4.2 software was used to quantify the environmental impacts of camelina seed and camelina methyl ester production.

Results and discussion

The results showed that greenhouse gas (GHG) emissions during camelina production in different regions vary between 49.39 and 472.51 kg CO₂-eq./ha due to differences in agro-climatic and weather variations. The GHG emissions for 1 kg of camelina produced in Corvallis, Pendleton, Pullman, and Sheridan were 0.76 ± 11, 0.55 ± 10, 0.47 ± 18, and 1.26 ± 6 % kg CO₂-eq., respectively. The GHG emissions for 1000 MJ of camelina biodiesel using camelina produced in Corvallis, Pendleton, Pullman, and Sheridan were 53.60 ± 5, 48.87 ± 5, 44.33 ± 7, and 78.88 ± 4 % kg CO₂-eq., respectively. Other impact categories such as acidification and ecotoxicity for 1000 MJ of camelina biodiesel varied across the regions by 43 and 103 %, respectively.

Conclusions

It can be concluded that process-based crop models such as DNDC in conjunction with Monte Carlo analysis are helpful tools to quantitatively estimate the influence of regional factors on field emissions which consequently can provide information about the expected variability in LCA results.

     

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.

     

Well-to-wheel GHG emissions and mitigation potential from light-duty vehicles in Macau

Purpose

The rapid growth of vehicle sales and usage has highlighted the need for greenhouse gas (GHG) emission reduction in Macau, a special administrative region (SAR) of China. As the most primary vehicle type, light-duty vehicles (LDV, including light-duty gasoline vehicles (LDGVs) and light-duty diesel vehicles (LDDVs)) play a key role in promoting the GHG reduction and development of green transportation system in Macau.

Methods

This study, on the basis of real-world tested and statistical data, firstly performed a streamlined life-cycle assessment (SLCA) on LDVs, to evaluate the potential GHG emissions and reduction through shifting to hybrid electric vehicles (HEVs) and electric vehicles (EVs).

Results and discussion

The results show that the mean GHG emissions from the LDGVs, LDDVs, and HEVs per 100 km were 25.16, 20.30, and 15.00 kg CO₂ eq, respectively. Under the current electricity mix in Macau, EVs with the emissions of 12.39 kg CO₂ eq/100 km can achieve a significant GHG emission reduction of LDVs in Macau. The total GHG emissions from LDVs increased from 124.99 to 247.82 thousand metric tons over the periods 2001–2014, with a 5.42% annual growth rate. A scenario analysis indicated that the development of HEVs and EVs—especially EVs—has the potential to control the GHG emissions from LDVs. Under the electricity mix of natural gas (NG) and solar energy (SE), the GHG emissions from EVs would drop by about 22 and 28%, respectively, by 2030.

Conclusions

This study develops a useful approach to evaluate the potential GHG emissions and its reduction strategies in Macau. All the obtained results could be useful for decision makers, providing robust support for drawing up an appropriate plan for improving green transportation systems in Macau.

     

Improving the accounting of field emissions in the carbon footprint of agricultural products: a comparison of default IPCC methods with readily available medium-effort modeling approaches

Purpose

The estimations of greenhouse gas (GHG) field emissions from fertilization and soil carbon changes are challenges associated with calculating the carbon footprint (CFP) of agricultural products. At the regional level, the IPCC Guidelines for National Greenhouse Gas Inventories (2006a) Tier 1 approach, based on default emission factors, insufficiently accounts for emission variability resulting from pedo-climatic conditions or management practices. However, Tier 2 and 3 approaches are usually considered too complex to be practicable. In this paper, we discuss different readily available medium-effort methods to improve the accuracy of GHG emission estimates.

Methods

We present four case studies—two wheat crops in Germany and two peach orchards in Italy—to test the performance of Tier 1, 2, and 3 methodologies and compare the estimated results with available field measurements. The methodologies selected at Tier 2 and Tier 3 level are characterized by simple implementation and data collection, for which only a medium level of effort for stakeholders is required. The Tier 2 method consists of calculating direct and indirect N₂O, emissions from fertilization with a multivariate empirical model which accounts for pedo-climatic and crop management conditions. The Tier 3 method entails simulation of soil carbon stock change using the Rothamsted carbon model.

Results and discussion

Relevant differences were found among the tested methodologies: in all case studies, the Tier 1 approach exceeded the Tier 2 estimations for fertilizer-induced emissions (up to +50 %) and the measurements. Using this higher Tier approach reduced the estimated CFP calculation of annual crops by 4 and 21 % and that of the perennial crop by 7 %. Removals related to positive soil carbon change calculated using the Tier 1 approach also exceeded the Tier 3 calculations for the studied annual crops (up to +90 %) but considerably underrated the Tier 3 estimations and measurements for perennial crops (?75 %). In this case, the impact of the selected Tier method on the final CFP results was even more relevant: an increase of 194 and 88 % for the studied annual crops and a decrease of 67 % for the perennial crop case study.

Conclusions

The use of higher Tiers for the estimation of land-based emissions is strongly recommended to improve the accuracy of the CFP results. The suggested medium-effort methods tested in this study represent a good compromise between complexity reduction and accuracy improvement and can be considered reliable for the assessment of GHG mitigation potentials.

     

Accounting for inter-annual <Emphasis Type="Italic">variability</Emphasis> of farm activity data for calculation of greenhouse gas emissions in dairy farming

Purpose

This study examines the inter-annual variability of production data in an organic dairy farm and its effect on the estimation of product-related greenhouse gas emissions (GHG) using a detailed material flow model. It is believed that the examination of only one production year may not adequately reflect temporal representativeness and may therefore lead to unreliable results. The current study also provides a method to deal with variability when temporal representativeness cannot be ensured.

Methods

All material flows related to milk production from six consecutive milk years in an organic dairy farm in northern Germany were analysed. The milk yield of the 75 to 91 cows varied between 5418 and 7102 kg energy corrected milk (ECM) per cow and year. GHG emissions were estimated using calculation guidelines from the International Dairy Federation (IDF) and the Intergovernmental Panel on Climate Change (IPCC). Emissions were calculated in the Flow Analysis and Resource Management (FARM) model ensuring mass balances for nitrogen and phosphorous in every subsection of the model. Based on the variability of crop yields, the number of years for representative average data was calculated as well as an uncertainty when only a limited number of years was available.

Results and discussion

Estimated GHG emissions varied between 0.88 and 1.09 kg CO₂-eq kg^?1 ECM^?1 (mean, standard deviation of the mean = 0.97 and 0.07 kg CO₂-eq kg^?1 ECM^?1). Emissions from ruminant digestion had the highest contribution (50.9 ± 2.3) percent in relation to overall product-related GHG emissions. Direct emissions from soil showed the highest coefficient of variation (36%) due to simultaneous changes in fertilization amount, crop yield and milk yield which showed no significant direct relationship. The number of years needed to be assessed for representative average yields was between 27 and 215 years for clover grass and maize silage, respectively. When performing a sensitivity analysis based on the variability of crop yields, the assessed farm showed reliable results with average data of at least 4 years.

Conclusions

Temporal representativeness should be dealt with explicitly in GHG assessments for dairy farming. If the representativeness of crop yields cannot be ensured, an uncertainty bandwidth of the results based on variability of yields can provide a basis for comparing different farms or farming systems. This approach could also be extended to other variabilities in dairy farming for more reliability of results.

     

Including GHG emissions from mangrove forests LULUC in LCA: a case study on shrimp farming in the Mekong Delta,Vietnam

Purpose

Mangrove forests have been recognized as important regulators of greenhouse gases (GHGs), yet the resulting land use and land-use change (LULUC) emissions have rarely been accounted for in life cycle assessment (LCA) studies. The present study therefore presents up-to-date estimates for GHG emissions from mangrove LULUC and applies them to a case study of shrimp farming in Vietnam.

Methods

To estimate the global warming impacts of mangrove LULUC, a combination of the International Panel for Climate Change (IPCC) guidelines, the Net Committed Emissions, and the Missed Potential Carbon Sink method were used. A literature review was then conducted to characterize the most critical parameters for calculating carbon losses, missed sequestration, methane fluxes, and dinitrogen monoxide emissions.

Results and discussion

Our estimated LUC emissions from mangrove deforestation resulted in 124 t CO₂ ha^?1 year^?1, assuming IPCC’s recommendations of 1 m of soil loss, and 96% carbon oxidation. In addition to this, 1.25 t of carbon would no longer be sequestered annually. Discounted over 20 years, this resulted in total LULUC emissions of 129 t CO₂ ha^?1 year^?1 (CV = 0.441, lognormal distribution (ln)). Shrimp farms in the Mekong Delta, however, can today operate for 50 years or more, but are 1.5 m deep (50% oxidation). In addition to this, Asian tiger shrimp farming in mixed mangrove concurrent farms (the only type of shrimp farm that resulted in mangrove deforestation since 2000 in our case study) resulted in 533 kg methane and 1.67 kg dinitrogen monoxide per hectare annually. Consequently, the LULUC GHG emissions resulted in 184 and 282 t CO₂-eq t^?1 live shrimp at farm gate, using mass and economic allocation, respectively. These GHG emissions are about an order of magnitude higher than from semi-intensive or intensive shrimp farming systems. Limitations in data quality and quantity also led us to quantify the uncertainties around our emission estimates, resulting in a CV of between 0.4 and 0.5.

Conclusions

Our results reinforce the urgency of conserving mangrove forests and the need to quantify uncertainties around LULUC emissions. It also questions mixed mangrove concurrent shrimp farming, where partial removal of mangrove forests is endorsed based upon the benefits of partial mangrove conservation and maintenance of certain ecosystem services. While we recognize that these activities limit the chances of complete removal, our estimates show that large GHG emissions from mangrove LULUC question the sustainability of this type of shrimp farming, especially since mixed mangrove farming only provide 5% of all farmed shrimp produced in Vietnam.

     

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.

     

Carbon footprint of pomegranate (<Emphasis Type="Italic">Punica granatum</Emphasis>) cultivation in a hyper-arid region in coastal Peru

Purpose

The cultivation of pomegranate worldwide has increased sharply in the past few years, mainly due to the growing perception that this fruit has numerous medical benefits. Despite the proliferation of studies delving into the properties of pomegranate from a medical and dietary perspective, its analysis from an environmental perspective has yet to be carried out in depth. Hence, the present study aims at understanding the life cycle environmental impacts in terms of greenhouse gas (GHG) emissions derived from the cultivation, processing and distribution abroad of fresh pomegranate grown at an innovative farm in a hyper-arid area in the region of Ica (Peru).

Methods

The international standards for life cycle methodologies were considered in order to obtain the overall carbon footprint (CFP) of fresh pomegranate cultivation, processing and distribution. Data acquisition was performed at the cultivation site and supported by the ecoinvent^® database, whereas GHG emissions were modelled using the IPCC 2007 method. In addition, biogenic carbon sequestration was included in the assessment, using two distinct models, a first one to model the aerial carbon sequestered by the pomegranate trees and a second, using the IPCC Soil Carbon Tool for soil storage.

Results and discussion

Annual results show that on-site GHG emissions can be mitigated to a great extent in the first years of production thanks to biogenic carbon sequestration. However, through time, this tendency is reverted, and in years of maximum pomegranate productivity, GHG emissions are estimated to outweigh those linked to sequestration, despite the relevant minimization of emissions when using innovative irrigation schemes as compared to the conventional flood irrigation in the region.

Conclusions

Despite the threat in terms of water depletion and security, the expansion of Peru’s agricultural frontier in hyper-arid areas appears to be a feasible strategy for carbon fixation, although current agricultural practices, such as the use of machinery or electricity, need to be optimized to make positive the carbon balance.

     

Updated and harmonised greenhouse gas emissions for crop inventories

Purpose

The emission of greenhouse gases (GHG) is a key criterion in the environmental assessment of biofuels. Life cycle inventories taking into account the latest methodological developments are an essential prerequisite for this assessment. In the last years, substantial progresses in the modelling of nitrogen emissions relevant for the climate as well as in modelling the emissions from land use change (LUC) have been achieved. Therefore, the biomass production inventories in the ecoinvent database were revised to take into account these developments.

Methods

The IPCC method tier 1 has been used for the assessment of N₂O emissions. Induced emissions from NH₃ and NO₃ were included as well. Due to the importance of the latter emissions for N₂O formation, these emissions have also been updated and harmonised. The Agrammon model was used for the NH₃ emissions. The SALCA-NO₃ model has been applied in the European inventories to estimate nitrate leaching, whilst in non-European inventories the SQCB-NO₃ model has been used. The quantification of the land use change areas has been based on annualized, retrospective data of the last 20 years. All carbon pools (from aboveground biomass to soil organic carbon) were considered and differentiated on a regional level for all of the natural vegetation categories affected. Whenever possible, default values and methods from the IPCC 2006 were applied.

Results and discussion

The changes for ammonia emissions were generally very small (?5 % on average). The nitrate emissions increased on average by +13 %, but this slight trend is the result of important downward and upward changes, whilst the average N₂O emissions decreased by ?26 %. For the existing inventories of soybean, palm oil and sugarcane production, significant increases of GHG emissions resulted from LUC modelling. This was mainly due to the consistent inclusion of all carbon stocks according to the IPCC guidelines. The calculation method can also result in important C sequestration effects in certain cases like African Jatropha production.

Conclusions

The changes in greenhouse gas emissions due to the updated methodology were significant. This shows that life cycle assessment studies for biofuels using older methodological bases need to be revised and could lead to different conclusions. The implemented and cultivated superstructure for LUC modelling is modular and flexible and can be easily extended to other important crop activities. The new parameterisation functionality applied for the activities provides powerful means for the simple generation of site-specific activities.

     

Estimation of greenhouse gas emissions from sewer pipeline system

Purpose

The aim of this study was to estimate the total greenhouse gas (GHG) emissions generated from whole life cycle stages of a sewer pipeline system and suggest the strategies to mitigate GHG emissions from the system.

Methods

The process-based life cycle assessment (LCA) with a city-scale inventory database of a sewer pipeline system was conducted. The GHG emissions (direct, indirect, and embodied) generated from a sewer pipeline system in Daejeon Metropolitan City (DMC), South Korea, were estimated for a case study. The potential improvement actions which can mitigate GHG emissions were evaluated through a scenario analysis based on a sensitivity analysis.

Results and discussion

The amount of GHG emissions varied with the size (150, 300, 450, 700, and 900 mm) and materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) of the pipeline. Pipes with smaller diameter emitted less GHG, and the concrete pipe generated lower amount of GHG than pipes made from other materials. The case study demonstrated that the operation (OP) stage (3.67 × 10⁴ t CO₂eq year^?1, 64.9%) is the most significant for total GHG emissions (5.65 × 10⁴ t CO₂eq year^?1) because a huge amount of CH₄ (3.51 × 10⁴ t CO₂eq year^?1) can be generated at the stage due to biofilm reaction in the inner surface of pipeline. Mitigation of CH₄ emissions by reducing hydraulic retention time (HRT), optimizing surface area-to-volume (A/V) ratio of pipes, and lowering biofilm reaction during the OP stage could be effective ways to reduce total GHG emissions from the sewer pipeline system. For the rehabilitation of sewer pipeline system in DMC, the use of small diameter pipe, combination of pipe materials, and periodic maintenance activities are suggested as suitable strategies that could mitigate GHG emissions.

Conclusions

This study demonstrated the usability and appropriateness of the process-based LCA providing effective GHG mitigation strategies at a city-scale sewer pipeline system. The results obtained from this study could be applied to the development of comprehensive models which can precisely estimate all GHG emissions generated from sewer pipeline and other urban environmental systems.

     

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.

     

N<Subscript>2</Subscript>O and CH<Subscript>4</Subscript> emission from <Emphasis Type="Italic">Miscanthus</Emphasis> energy crop fields in the infertile Loess Plateau of China

Background

The greenhouse gas (GHG) mitigation is one of the most important environmental benefits of using bioenergy replacing fossil fuels. Nitrous oxide (N₂O) and methane (CH₄) are important GHGs and have drawn extra attention for their roles in global warming. Although there have been many works of soil emissions of N₂O and CH₄ from bioenergy crops in the field scale, GHG emissions in large area of marginal lands are rather sparse and how soil temperature and moisture affect the emission potential remains unknown. Therefore, we sought to estimate the regional GHG emission based on N₂O and CH₄ releases from the energy crop fields.

Results

Here we sampled the top soils from two Miscanthus fields and incubated them using a short-term laboratory microcosm approach under different conditions of typical soil temperatures and moistures. Based on the emission measurements of N₂O and CH₄, we developed a model to estimate annual regional GHG emission of Miscanthus production in the infertile Loess Plateau of China. The results showed that the N₂O emission potential was 0.27 kg N ha^?1 year^?1 and clearly lower than that of croplands and grasslands. The CH₄ uptake potential was 1.06 kg C ha^?1 year^?1 and was slightly higher than that of croplands. Integrated with our previous study on the emission of CO₂, the net greenhouse effect of three major GHGs (N₂O, CH₄ and CO₂) from Miscanthus fields was 4.08 t CO_2eq ha^?1 year^?1 in the Loess Plateau, which was lower than that of croplands, grasslands and shrub lands.

Conclusions

Our study revealed that Miscanthus production may hold a great potential for GHG mitigation in the vast infertile land in the Loess Plateau of China and could contribute to the sustainable energy utilization and have positive environmental impact on the region.

     

Life cycle assessment of renewable diesel production from lignocellulosic biomass

Purpose

Governments around the world encourage the use of biofuels through fuel standard policies that require the addition of renewable diesel in diesel fuel from fossil fuels. Environmental impact studies of the conversion of biomass to renewable diesel have been conducted, and life cycle assessments (LCA) of the conversion of lignocellulosic biomass to hydrogenation-derived renewable diesel (HDRD) are limited, especially for countries with cold climates like Canada.

Methods

In this study, an LCA was conducted on converting lignocellulosic biomass to HDRD by estimating the well-to-wheel greenhouse gas (GHG) emissions and fossil fuel energy input of the production of biomass and its conversion to HDRD. The approach to conduct this LCA includes defining the goal and scope, compiling a life cycle inventory, conducting a life cycle impact assessment, and executing a life cycle interpretation. All GHG emissions and fossil fuel energy inputs were based on a fast pyrolysis plant capacity of 2000 dry tonnes biomass/day. A functional unit of 1 MJ of HDRD produced was adopted as a common unit for data inputs of the life cycle inventory. To interpret the results, a sensitivity analysis was performed to measure the impact of variables involved, and an uncertainty analysis was performed to assess the confidence of the results.

Results and discussion

The GHG emissions of three feedstocks studied—whole tree (i.e., chips from cutting the whole tree), forest residues (i.e., chips from branches and tops generated from logging operations), and agricultural residues (i.e., straw from wheat and barley)—range from 35.4 to 42.3 g CO_2,eq/MJ of HDRD (i.e., lowest for agricultural residue- and highest for forest residue-based HDRD); this is 53.4–61.1 % lower than fossil-based diesel. The net energy ratios range from 1.55 to 1.90 MJ/MJ (i.e., lowest for forest residue- and highest for agricultural residue-based HDRD) for HDRD production. The difference in results among feedstocks is due to differing energy requirements to harvest and pretreat biomass. The energy-intensive hydroprocessing stage is responsible for most of the GHG emissions produced for the entire conversion pathway.

Conclusions

Comparing feedstocks showed the significance of the efficiency in the equipment used and the physical properties of biomass in the production of HDRD. The overall results show the importance of efficiency at the hydroprocessing stage. These findings indicate significant GHG mitigation benefits for the oil refining industry using available lignocellulosic biomass to produce HDRD for transportation fuel.

     

Nitrous oxide emissions during the non-rice growing seasons of two subtropical rice-based rotation systems in southwest China

Background and aims

High nitrous oxide (N₂O) emissions may occur during the non-rice growing season of Chinese rice-upland crop rotation systems. However, our understanding of N₂O emission during this season is poor due to a scarcity of available field N₂O measurements.

Methods

Using the static manual chamber-GC technique, seasonal N₂O emissions during the non-rice growing season were simultaneously measured at two adjacent rice-wheat and rice-rapeseed fields in southwest China for three consecutive annual rotation cycles (May 2005 to May 2008).

Results

Compared to the control, N fertilizer applications significantly enhanced soil N₂O emissions from both wheat and rapeseed systems. Seasonal cumulative N₂O fluxes from wheat systems were on average 2.6 kg N ha^?1 for the recommended practice (RP [150 kg N ha^?1]) and 5.0 kg N ha^?1 for the conventional practice (CP [250 kg N ha^?1]). Lower N₂O emissions were observed from the adjacent rapeseed systems. Average cumulative seasonal N₂O fluxes from rapeseed were 1.5 and 2.2 kg N ha^?1 for the RP and CP treatments, respectively. The first 3 weeks after N fertilization were the “hot moment” of N₂O emissions for both the wheat and rapeseed systems. The lowest yield-scaled N₂O fluxes for wheat were obtained at the RP treatment (mean: 0.81 kg N Mg^?1) while for rapeseed the CP treatment produced the lowest yield-scaled fluxes (mean: 0.79 kg N Mg^?1). On average, the direct N₂O emission factors (EF_d) for the wheat system (1.76 %) were over two times higher than for the rapeseed system (0.73 %).

Conclusions

Intercropping of rapeseed tends to result in lower N₂O emissions than wheat for rice-upland crop rotation systems of southwest China, indicating that either the N fertilization or the cropping system need to be considered not only for improving the estimate of regional and/or national N₂O fluxes but also for proposing the climate-smart agricultural management practice to reduce N₂O emissions from agricultural soils.     

Estimating the global warming emissions of the LCAXVII conference: connecting flights matter

Purpose

Conferences are an important element of scientific activity but can also be a major cause of environmental burden. With this in mind, we analysed the global warming emissions of the 2017 annual conference of the American Center for Life Cycle Assessment (ACLCA), in order to estimate the carbon footprint and identify potential ways to reduce it.

Methods

We used survey data from participants as well as literature sources to complete an attributional assessment of the greenhouse gas emissions per participant. A method to calculate the ‘ideal’ location is proposed, which can be used to identify ‘unreasonably’ distant conference locations.

Results and discussion

The average emissions per participant were found to be 952 kg CO_2eq, but with a large variability due to differences in travelled distance. Connecting flights were found to increase emissions up to 32% compared to direct flights, due to the increased number of take-offs and landings.

Conclusions

Results indicate that future studies should use distance-dependent flight emissions to increase the accuracy of the assessment. Some measures, such as meat-free menus, had a relatively minor contribution to emission reductions, but could be important as scientists advocating for the reduction of environmental burden should lead by example.

     

FoodPrints of households

Purpose

Food consumption is one of the main drivers of environmental impacts. To develop meaningful strategies for the reduction of impacts, food consumption patterns need to be understood on the household level, as purchasing decisions are taken on this level. The goals of this study were to develop a model that estimates food demand and environmental impact as a function of household characteristics, to assess variability between households, and to provide a basis for the development of consumer-targeted political interventions. We titled the study “FoodPrints of households,” as we assessed food consumption in terms of carbon footprint (in analogy to (Stoessel et al. Environ Sci Technol 46(6):3253–3262 2012)).

Methods

We used data from the Swiss household budget survey and applied multiple linear regressions based on generalized linear models to quantify food and beverage demand of individual households. Seven household characteristics, such as size, income, and educational level, served as input variables for the regressions. In a case study, food and beverage demand of 3238 individual households of a Swiss municipality was environmentally assessed with life cycle assessment, and scenarios for different reduction strategies were evaluated.

Results and discussion

We found that the carbon footprints of in-home food consumption per household member and year vary from 0.08 t CO₂ eq. to 5 t CO₂ eq. with a median value of 1 t CO₂ eq. This variability is significantly smaller than the carbon footprint variability for the consumption areas of housing and mobility, where 25 % of the people are responsible for 50 % of the environmental impacts. Differences between high- and low-impact households can be primarily explained by differences in meat and dairy consumption.

Conclusions

This paper presents a model for quantifying food demand and impacts on a household level in Switzerland and represents a basis for developing targeted political measures to mitigate food consumption impacts. Household budget data is also available for many other countries, and the methods presented in this paper could therefore also be applied to other geographical regions.

     

Evaluating the carbon footprint of Chilean organic blueberry production

Purpose

Chile is the second largest blueberry producer and exporter worldwide. At the global level, there is a lack of information by means of field data about greenhouse gas emissions from organic cultivation of this fruit. This study obtains a resource use inventory and assesses the cradle-to-farm gate carbon footprint (CF) of organic blueberry (Vaccinium corymbosum) production in the main cultivation area of Chile in order to identify CF key factors and to provide improvement measures.

Methods

The method used in this study follows the ISO 14040 framework and the main recommendations in the PAS 2050 guide as well as its specification for horticultural products PAS 2050-1. Primary data were collected for three consecutive production seasons from five organic Chilean blueberry orchards and calculations conducted with the GaBi 4 software. Agricultural factors such as fertilizers, pesticides, fossil fuels, electricity, materials, machinery, and direct land use change (LUC) are included. Only three orchards present direct LUC.

Results and discussion

The direct LUC associated with the conversion from annual crops to perennial crops is a key factor in the greenhouse gas removals from the orchards. When accounting for direct LUC, the CF of organic blueberry production in the studied orchards ranges from removals (reported as negative value) of ?0.94 to emissions of 0.61 kg CO₂-e/kg blueberry. CF excluding LUC ranges from 0.27 to 0.69 kg CO₂-e/kg blueberry. The variability in the results of the orchards suggests that the production practices have important effects on the CF. The factors with the greatest contribution to the greenhouse emissions are organic fertilizers followed by energy use causing, on average, 50 and 43 % of total emissions, respectively.

Conclusions

The CF of the organic blueberry orchards under study decreases significantly when taking into account removals related to LUC. The results highlight the importance of reporting separately the greenhouse gas (GHG) emissions from LUC. The CF of blueberry production could be reduced by optimizing fertilizer application, using cover crops and replacing inefficient tractors and large irrigation pumps. The identification of improvement measures would be a useful guide for changing grower practices.

     

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.     

Life cycle assessment of biodiesel production from beef tallow in Brazil

Purpose

Renewable energy sources, particularly biofuels, are being promoted as possible solutions to address global warming and the depletion of petroleum resources. In this context, biodiesel is a solution to the growing demand for renewable fuels. Beef tallow is the second leading raw material after soybean oil used in biodiesel production in Brazil. Evaluating and addressing the environmental impacts of beef tallow biodiesel are of great importance for its life cycle impact assessment (LCIA).

Methods

Inventory data on tallow and biodiesel production were collected from the literature and from a primary data source provided by a Brazilian biodiesel plant. The modeled system represents the Brazilian reality for the 2005–2015 decade. Subsequently, the environmental impacts of beef tallow biodiesel production were characterized for a selection of environmental impact indicators: global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), and water footprint (assessed based on blue water use (BWU) and blue water consumption (BWC) indicators). From the characterization of these environmental burdens, the main sources of environmental impact were evaluated. Sensitivity analysis was conducted to verify the influence of key parameters (emission factor, energy consumption, and prices) on changes in the environmental load of beef tallow biodiesel.

Results and discussion

Carbon flux results indicate that beef tallow biodiesel production acts as a carbon source. Namely, pasture carbon uptake (91% of all carbon input) is lower than combined biogenic and fossil CO₂ emissions, which are controlled by cattle enteric fermentation as methane (72%) and by thermal energy processes (25%). Otherwise, thermal energy production accounts for 80% of total AP emissions, and cattle urine and manure are responsible for 70% of total EP emissions. The BWC and BWU water footprints of the whole process are controlled by electricity usage, which was greater than 90% for each indicator due to the high proportion of total energy (70%) derived from hydropower in Brazil. The environmental burden from transportation is minimal compared to other processes. Tallow biodiesel GWP can be improved if the carbon uptake potential from grass and low fertilizer utilization are accurately considered, as observed in the sensitivity analysis. For each MJ of beef tallow biodiesel produced, 4.6 g of CO₂ is released to the atmosphere.

Conclusions

Methane emissions, mainly due to cattle enteric fermentation, and thermal energy processes at the industrial units were the main sources of environmental GWP, AP, and EP impacts. Otherwise, water footprint indicators were associated with the high proportion of total energy derived from hydropower in Brazil.

     

Life cycle energy use and CO<Subscript>2</Subscript> emissions of small-scale gold mining and refining processes in the Philippines

Purpose

Gold is one of the most significant metals in the world, with use in various sectors including the electronic, health, and fashion industries. The Philippines has the world’s third largest known Au deposits and is ranked 20th in global gold production. Of the country’s annual production, about 80% is from the small-scale gold mining (SSGM) sector. This work estimates the first location-specific life cycle energy use and CO₂ emissions of SSGM establishments in the Philippines.

Methods

Process-based LCA was used with functional unit of 100 g Au and observed data from 2010 to 2011 for mining, comminution, recovery, and refining. Four gold production paths were observed in the provinces of Benguet and Camarines Norte, namely, amalgamation, cyanidation with carbon-in-leach (CIL), cyanidation with leaching with zinc, and combination of amalgamation and cyanidation with CIL.

Results and discussion

It was estimated that 3–18 g of Au was extracted for every ton of ore within 57–159 man-hours from mining to refining. Energy use estimates ranged from 3501 to 67,325 MJ/100 g Au, while CO₂ emission estimates ranged from 398 to 5340 kg CO₂/100 g Au. The combination of amalgamation and cyanidation with CIL processes was the least energy and carbon intensive, while cyanidation with CIL process was the most intensive. Electricity use accounted for 95–100% of total emissions, except in cyanidation with CIL where kerosene accounts for 77% of the total. Since SSGMs contributed 80% of the 40 tons of Au produced in the Philippines in 2014, the SSGM energy use was estimated to be between 1120 and 21,544 TJ and the CO₂ emissions to be between 129 and 1726 ktons CO₂. Energy estimates are most sensitive to refining process yield and electrical equipment efficiency.

Conclusions

The estimated life cycle emissions rate for SSGM in the Philippines is lower than available estimates of large-scale mining. Notwithstanding, given the sector’s reliance on fossil fuels for its energy needs and the Philippines’ pledge to reduce its CO₂ footprint by 70% in 2030, every effort to mitigate energy use and CO₂ emission counts. Three main recommendations toward energy consumption and CO₂ emissions reduction in SSGMs are proposed: (1) policy to promote technologies that are energy-efficient and processes that maximize gold process yield, (2) effective Minahang Bayan (SSGM mining zone mandated by law) implementation to ensure use of higher-grade ores, and (3) adoption of renewable energy in Minahang Bayans to promote energy independence and mitigate CO₂ emissions.