An appraisal of carbon footprint of milk from commercial grass-based dairy farms in Ireland according to a certified life cycle assessment methodology

Purpose

Life cycle assessment (LCA) studies of carbon footprint (CF) of milk from grass-based farms are usually limited to small numbers of farms (<30) and rarely certified to international standards, e.g. British Standards Institute publicly available specification 2050 (PAS 2050). The goals of this study were to quantify CF of milk from a large sample of grass-based farms using an accredited PAS 2050 method and to assess the relationships between farm characteristics and CF of milk.

Materials and methods

Data was collected annually using on-farm surveys, milk processor records and national livestock databases for 171 grass-based Irish dairy farms with information successfully obtained electronically from 124 farms and fed into a cradle to farm-gate LCA model. Greenhouse gas (GHG) emissions were estimated with the LCA model in CO₂ equivalents (CO₂-eq) and allocated economically between dairy farm products, except exported crops. Carbon footprint of milk was estimated by expressing GHG emissions attributed to milk per kilogram of fat and protein-corrected milk (FPCM). The Carbon Trust tested the LCA model for non-conformities with PAS 2050. PAS 2050 certification was achieved when non-conformities were fixed or where the effect of all unresolved non-conformities on CF of milk was?<?±5 %.

Results and discussion

The combined effect of LCA model non-conformities with PAS 2050 on CF of milk was <1 %. Consequently, PAS 2050 accreditation was granted. The mean certified CF of milk from grass-based farms was 1.11 kg of CO₂-eq/kg of FPCM, but varied from 0.87 to 1.72 kg of CO₂-eq/kg of FPCM. Although some farm attributes had stronger relationships with CF of milk than the others, no attribute accounted for the majority of variation between farms. However, CF of milk could be reasonably predicted using N efficiency, the length of the grazing season, milk yield/cow and annual replacement rate (R ²?=?0.75). Management changes can be applied simultaneously to improve each of these traits. Thus, grass-based farmers can potentially significantly reduce CF of milk.

Conclusions

The certification of an LCA model to PAS 2050 standards for grass-based dairy farms provides a verifiable approach to quantify CF of milk at a farm or national level. The application of the certified model highlighted a wide range between the CF of milk of commercial farms. However, differences between farms’ CF of milk were explained by variation in various aspects of farm performance. This implies that improving farm efficiency can mitigate CF of milk.     

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.

     

Climate change impacts on life cycle greenhouse gas (GHG) emissions savings of biomethanol from corn and soybean

Purpose

The purpose of this study is to assess and calculate the potential impacts of climate change on the greenhouse gas (GHG) emissions reduction potentials of combined production of whole corn bioethanol and stover biomethanol, and whole soybean biodiesel and stalk biomethanol. Both fuels are used as substitutes to conventional fossil-based fuels. The product system includes energy crop (feedstock) production and transportation, biofuels processing, and biofuels distribution to service station.

Methods

The methodology is underpinned by life cycle thinking. Crop system model and life cycle assessment (LCA) model are linked in the analysis. The Decision Support System for Agrotechnology Transfer – crop system model (DSSAT-CSM) is used to simulate biomass and grain yield under different future climate scenarios generated using a combination of temperature, precipitation, and atmospheric CO₂. Historical weather data for Gainesville, Florida, are obtained for the baseline period (1981–1990). Daily minimum and maximum air temperatures are projected to increase by +2.0, +3.0, +4.0, and +5.0 °C, precipitation is projected to change by ±20, 10, and 5 %, and atmospheric CO₂ concentration is projected to increase by +70, +210, and +350 ppm. All projections are made throughout the growing season. GaBi 4.4 is used as primary LCA modelling software using crop yield data inputs from the DSSAT-CSM software. The models representation of the physical processes inventory (background unit processes) is constructed using the ecoinvent life cycle inventory database v2.0.

Results and discussion

Under current baseline climate condition, net greenhouse gas (GHG) emissions savings per hectare from corn-integrated biomethanol synthesis (CIBM) and soybean-integrated biomethanol synthesis (SIBM) were calculated as ?8,573.31 and ?3,441 kg CO₂-eq. ha^?1 yr^?1, respectively. However, models predictions suggest that these potential GHG emissions savings would be impacted by changing climate ranging from negative to positive depending on the crop and biofuel type, and climate scenario. Increased atmospheric level of CO₂ tends to minimise the negative impacts of increased temperature.

Conclusions

While policy measures are being put in place for the use of renewable biofuels driven by the desire to reduce GHG emissions from the use of conventional fossil fuels, climate change would also have impacts on the potential GHG emissions reductions resulting from the use of these renewable biofuels. However, the magnitude of the impact largely depends on the biofuel processing technology and the energy crop (feedstock) type.     

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.

     

Mitigation of greenhouse gas emissions from reed canary grass in paludiculture: effect of groundwater level

Background and aims

Combination of rewetting and wetland crop cultivation (paludiculture) is pursued as a wider carbon dioxide (CO₂) mitigation option in drained peatland. However, information on the overall greenhouse gas (GHG) balance for paludiculture is lacking. We investigated the GHG balance of peatlands grown with reed canary grass (RCG) and rewetted to various extents.

Methods

Gas fluxes of CO₂, methane (CH₄) and nitrous oxide (N₂O) were measured with a static chamber technique for 10 months from mesocosms sown with RCG and manipulated to ground water levels (GWL) of 0, ?10, ?20, ?30 and ?40 cm below the soil surface. Gross primary production (GPP) was estimated from the above ground biomass yield.

Results

The mean dry biomass yield across all water table treatments was 6 Mg ha^?1 with no significant differences between the treatments. Raising the GWL to the surface decreased both the net ecosystem exchange (NEE) of CO₂ and N₂O emissions whereas CH₄ emissions increased. Total cumulative GHG emissions (for 10 months) corresponded to 0.08, 0.13, 0.61, 0.68 and 0.98 kg CO₂ equivalents m^?2 from the GWL treatments at 0, ?10, ?20, ?30 and ?40 cm below the soil surface, respectively.

Conclusions

The results showed that a reduction in total GHG emission can be achieved without losing the productivity of newly established RCG when GWL is maintained close to the surface. Further studies should address the practical constrains and long-term productivity of RCG cultivation in rewetted peatlands.     

Life-cycle greenhouse gas inventory analysis of household waste management and food waste reduction activities in Kyoto, Japan

Purpose

Source-separated collection of food waste has been reported to reduce the amount of household waste in several cities including Kyoto, Japan. Food waste can be reduced by various activities including preventing edible food loss, draining moisture, and home composting. These activities have different potentials for greenhouse gas (GHG) reduction. Therefore, we conducted a life-cycle inventory analysis of household waste management scenarios for Kyoto with a special emphasis on food waste reduction activities.

Methods

The primary functional unit of our study was ??annual management of household combustible waste in Kyoto, Japan.?? Although some life-cycle assessment scenarios included food waste reduction measures, all of the scenarios had an identical secondary functional unit, ??annual food ingestion (mass and composition) by the residents of Kyoto, Japan.?? We analyzed a typical incineration scenario (Inc) and two anaerobic digestion (dry thermophilic facilities) scenarios involving either source-separated collection (SepBio) or nonseparated collection followed by mechanical sorting (MecBio). We assumed that the biogas from anaerobic digestion was used for power generation. In addition, to evaluate the effects of waste reduction combined with separate collection, three food waste reduction cases were considered in the SepBio scenario: (1) preventing loss of edible food (PrevLoss); (2) draining moisture contents (ReducDrain); and (3) home composting (ReducHcom). In these three cases, we assumed that the household waste was reduced by 5%.

Results and discussion

The GHG emissions from the Inc, MecBio, and SepBio scenarios were 123.3, 119.5, and 118.6 Gg CO₂-eq/year, respectively. Compared with the SepBio scenario without food waste reduction, the PrevLoss and ReducDrain cases reduced the GHG emissions by 17.1 and 0.5 Gg CO₂-eq/year. In contrast, the ReducHcom case increased the GHG emissions by 2.1 Gg CO₂-eq/year. This is because the biogas power production decreased due to the reduction in food waste, while the electricity consumption increased in response to home composting. Sensitivity analyses revealed that a reduction of only 1% of the household waste by food loss prevention has the same GHG reduction effect as a 31-point increase (from 50% to 81%) in the food waste separation rate.

Conclusions

We found that prevention of food losses enhanced by separate collection led to a significant reduction in GHG emissions. These findings will be useful in future studies designed to develop strategies for further reductions in GHG emissions.     

Greenhouse gas emissions from forestry in East Norway

Purpose

So far no calculations have been made for greenhouse gas (GHG) emissions from forestry in East Norway. This region stands for 80 % of the Norwegian timber production. The aim of this study was to assess the annual GHG emissions of Norwegian forestry in the eastern parts of the country from seed production to final felling and transport of timber to sawmill and wood processing industry (cradle-to-gate inventory), based on specific Norwegian data.

Methods

The life cycle inventory was conducted with SimaPro applying primary and secondary data from Norwegian forestry. GHG emissions of fossil-related inputs from the technosphere were calculated for the functional unit of 1 m³ timber extracted and delivered to industry gate in East Norway in 2010. The analysis includes seed and seedling production, silvicultural operations, forest road construction and upgrading, thinning, final felling, timber forwarding and timber transport on road and rail from the forest to the industry. Norwegian time studies of forestry machines and operations were used to calculate efficiency, fuel consumption and transport distances. Due to the lack of specific Norwegian data in Ecoinvent, we designed and constructed unit processes based on primary and secondary data from forestry in East Norway.

Results and discussion

GHG emissions from forestry in East Norway amounted to 17.893 kg CO₂-equivalents per m³ of timber delivered to industry gate in 2010. Road transport of timber accounted for almost half of the total GHG emissions, final felling and forwarding for nearly one third of the GHG emissions. Due to longer road transport distances, pulpwood had higher impact on the climate change category than saw timber. The construction of forest roads had the highest impact on the natural land transformation category. The net CO₂ emissions of fossil CO₂ corresponded to 2.3 % of the CO₂ sequestered by 1 m³ of growing forest trees and were compared to a calculation of biogenic CO₂ release from the forest floor as a direct consequence of harvesting.

Conclusions

Shorter forwarding and road transport distances, increased logging truck size and higher proportion of railway transport may result in lower emissions per volume of transported timber. A life cycle assessment of forestry may also consider impacts on environmental categories other than climate change. Biogenic CO₂ emissions from the soil may be up to 10 times higher than the fossil-related emissions, at least in a short-term perspective, and are highly dependent on stand rotation length.     

Reference and functional unit can change bioenergy pathway choices

Purpose

This study aims to compare the life cycle greenhouse gas (GHG) emissions of two cellulosic bioenergy pathways (i.e., bioethanol and bioelectricity) using different references and functional units. It also aims to address uncertainties associated with a comparative life cycle analysis (LCA) for the two bioenergy pathways.

Methods

We develop a stochastic, comparative life cycle GHG analysis model for a switchgrass-based bioenergy system. Life cycle GHG offsets of the biofuel and bioelectricity pathways for cellulosic bioenergy are compared. The reference system for bioethanol is the equivalent amount of gasoline to provide the same transportation utility (e.g., vehicle driving for certain distance) as bioethanol does. We use multiple reference systems for bioelectricity, including the average US grid, regional grid in the USA according to the North American Electric Reliability Corporation (NERC), and average coal-fired power generation, on the basis of providing the same transportation utility. The functional unit is one unit of energy content (MJ). GHG offsets of bioethanol and bioelectricity relative to reference systems are compared in both grams carbon dioxide equivalents per hectare of land per year (g CO₂-eq/ha-yr) and grams carbon dioxide equivalents per vehicle kilometer traveled (g CO₂-eq/km). For the latter, we include vehicle cycle to make the comparison meaningful. To address uncertainty and variability, we derive life cycle GHG emissions based on probability distributions of individual parameters representing various unit processes in the life cycle of bioenergy pathways.

Results and discussion

Our results show the choice of reference system and functional unit significantly changes the competition between switchgrass-based bioethanol and bioelectricity. In particular, our results show that the bioethanol pathway produces more life cycle GHG emissions than the bioelectricity pathway on a per unit energy content or a per unit area of crop land basis. However, the bioethanol pathway can offer more GHG offsets than the bioelectricity pathway on a per vehicle kilometer traveled basis when using bioethanol and bioelectricity for vehicle operation. Given the current energy mix of regional grids, bioethanol can potentially offset more GHG emissions than bioelectricity in all grid regions of the USA.

Conclusions

The reference and functional unit can change bioenergy pathway choices. The comparative LCA of bioenergy systems is most useful for decision support only when it is spatially explicit to address regional specifics and differences. The difference of GHG offsets from bioethanol and bioelectricity will change as the grid evolves. When the grids get cleaner over time, the favorability of bioethanol for GHG offsets increases.     

Understory vegetation management affected greenhouse gas emissions and labile organic carbon pools in an intensively managed Chinese chestnut plantation

Background and aims

The impact of understory vegetation control or replacement with selected plant species, which are common forest plantation management practices, on soil C pool and greenhouse gas (GHG, including CO₂, CH₄ and N₂O) emissions are poorly understood. The objective of this paper was to investigate the effects of understory vegetation management on the dynamics of soil GHG emissions and labile C pools in an intensively managed Chinese chestnut (Castanea mollissima Blume) plantation in subtropical China.

Methods

A 12-month field experiment was conducted to study the dynamics of soil labile C pools and GHG emissions in a Chinese chestnut plantation under four different understory management practices: control (Control), understory removal (UR), replacement of understory vegetation with Medicago sativa L. (MS), and replacement with Lolium perenne L. (LP). Soil GHG emissions were determined using the static chamber/GC technique.

Results

Understory management did not change the seasonal pattern of soil GHG emissions; however, as compared with the Control, the UR treatment increased soil CO₂ and N₂O emissions and CH₄ uptake, and the MS and LP treatments increased CO₂ and N₂O emissions and reduced CH₄ uptake (P?<?0.05 for all treatment effects, same below). The total global warming potential (GWP) of GHG emissions in the Control, UR, MS, and LP treatments were 36.56, 39.40, 42.36, and 42.99 Mg CO₂ equivalent (CO₂-e) ha^?1 year^?1, respectively, with CO₂ emission accounting for more than 95 % of total GWP regardless of the understory management treatment. The MS and LP treatments increased soil organic C (SOC), total N (TN), soil water soluble organic C (WSOC) and microbial biomass C (MBC), while the UR treatment decreased SOC, TN and NO₃ ^?-N but had no effect on WSOC and MBC. Soil GHG emissions were correlated with soil temperature and WSOC across the treatments, but had no relationship with soil moisture content and MBC.

Conclusions

Although replacing competitive understory vegetation with legume or less competitive non-legume species increased soil GHG emissions and total GWP, such treatments also increased soil C and N pools and are therefore beneficial for increasing soil C storage, maintaining soil fertility, and enhancing the productivity of Chinese chestnut plantations.     

Life cycle assessment of bio-based ethanol produced from different agricultural feedstocks

Purpose

Bio-based products are often considered sustainable due to their renewable nature. However, the environmental performance of products needs to be assessed considering a life cycle perspective to get a complete picture of potential benefits and trade-offs. We present a life cycle assessment of the global commodity ethanol, produced from different feedstock and geographical origin. The aim is to understand the main drivers for environmental impacts in the production of bio-based ethanol as well as its relative performance compared to a fossil-based alternative.

Methods

Ethanol production is assessed from cradle to gate; furthermore, end-of-life emissions are also included in order to allow a full comparison of greenhouse gas (GHG) emissions, assuming degradation of ethanol once emitted to air from household and personal care products. The functional unit is 1 kg ethanol, produced from maize grain in USA, maize stover in USA, sugarcane in North-East of Brazil and Centre-South of Brazil, and sugar beet and wheat in France. As a reference, ethanol produced from fossil ethylene in Western Europe is used. Six impact categories from the ReCiPe assessment method are considered, along with seven novel impact categories on biodiversity and ecosystem services (BES).

Results and discussion

GHG emissions per kilogram bio-based ethanol range from 0.7 to 1.5 kg CO₂ eq per kg ethanol and from 1.3 to 2 kg per kg if emissions at end-of-life are included. Fossil-based ethanol involves GHG emissions of 1.3 kg CO₂ eq per kg from cradle-to-gate and 3.7 kg CO₂ eq per kg if end-of-life is included. Maize stover in USA and sugar beet in France have the lowest impact from a GHG perspective, although when other impact categories are considered trade-offs are encountered. BES impact indicators show a clear preference for fossil-based ethanol. The sensitivity analyses showed how certain methodological choices (allocation rules, land use change accounting, land use biomes), as well as some scenario choices (sugarcane harvest method, maize drying) affect the environmental performance of bio-based ethanol. Also, the uncertainty assessment showed that results for the bio-based alternatives often overlap, making it difficult to tell whether they are significantly different.

Conclusions

Bio-based ethanol appears as a preferable option from a GHG perspective, but when other impacts are considered, especially those related to land use, fossil-based ethanol is preferable. A key methodological aspect that remains to be harmonised is the quantification of land use change, which has an outstanding influence in the results, especially on GHG emissions.     

Spatial and technological variability in the carbon footprint of durum wheat production in Iran

Purpose

The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran.

Methods

The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N₂O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat.

Results and discussion

The average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO₂-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO₂-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of ?2/3. This indicates that the carbon footprint of durum wheat production (in kg CO₂-eq kg^?1) typically decreases by 67% with a 100% increase in yield (in kg ha^?1 year^?1).

Conclusions

Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.

     

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

The increasing attention for global warming is likely to contribute to the introduction of policies or other incentives to reduce greenhouse gas (GHG) emissions related to livestock production, including dairy. The dairy sector is an important contributor to GHG emissions. Clinical mastitis (CM), an intramammary infection, results in reduced milk production and fertility, increases culling and mortality of cows and, therefore, has a negative impact on the efficiency (output/input) of milk production. This may increase GHG emissions per unit of product. Our objective was to estimate the impact of CM in dairy cows on GHG emissions of milk production for the Dutch situation. A dynamic stochastic simulation model was developed to simulate the dynamics and losses of CM for individual lactations. Cows receive a parity (1 to 5+), a milk production and a calving interval (CI). Based on the parity, cows have a risk of CM, with a maximum of three cases in a lactation. Pathogens causing CM were classified as gram-positive bacteria, gram-negative bacteria, or other. Based on the parity and pathogen combinations, cows had a reduced milk production, discarded milk, prolonged CI and a risk of removal (culling and mortality) that reduce productivity of dairy cows and therefore increase GHG emissions per unit of product. Using life cycle assessment, emissions of GHGs were estimated from cradle to farm gate for processes along the milk production chain that are affected by CM. Processes included were feed production, enteric fermentation, and manure management. Emissions of GHGs were expressed as kg CO₂ equivalents per ton of fat-and-protein-corrected milk (kg CO₂e/t FPCM). Emissions of cows with CM increased on average by 57.5 (6.2%) kg CO₂e/t FPCM compared with cows without CM. This increase was caused by removal (39%), discarded milk (38%), reduced milk production (17%) and prolonged CI (6%). The GHG emissions increased by 48 kg CO₂e/t FPCM for cows with one case of CM, by 69 kg CO₂e/t FPCM for cows with two cases of CM and by 92 kg CO₂e/t FPCM for cows with three cases of CM compared with cows without CM. Preventing CM can be an effective strategy for farmers to reduce GHG emissions and can contribute to sustainable development of the dairy sector, because this also can improve the income of farmers and the welfare of cows. The impact of CM on GHG emissions, however, will vary between farms due to environmental conditions and management practices.     

A comparison of the GHG emissions caused by manufacturing tissue paper from virgin pulp or recycled waste paper

Purpose

The aim of this work is to compare greenhouse gas (GHG) emissions from producing tissue paper from virgin pulp (VP) or recycled waste paper (RWP). In doing so, the study aims to inform decision makers at both company and national levels which are the main causes of emissions and to suggest the actions required to reduce pollution.

Methods

An attributional life cycle assessment (LCA) was performed in order to estimate and compare the GHG emissions of the two processes. LCA allows us to assess how the choice of raw material for VP and RWP processes influences total GHG emissions of tissue paper production, what are the main drivers behind these emissions and how do the direct materials; energy requirements and transportation contribute to the generation of emissions. The cradle-to-gate approach is carried out.

Results and discussion

The results show that demands for both thermal energy and electricity are higher for the RWP than for the VP if only the manufacturing stages are considered. However, a different picture emerges when the analysis looks at the entire life cycle of the production. GHG from the VP are about 30 % higher than the RWP, over the life cycle emitting 568 kg CO₂ eq more per kilogram of tissue paper. GHG emissions from the wood pulping alone were 559 g CO₂ eq per kilogram of tissue paper, three times higher than waste paper collection and transportation.

Conclusions

In terms of GHG emissions from cradle to gate, the recycled process less intensive than the virgin one for two reasons. First, as shown in the results the total GHG emissions from RWP are lower than those from VP due to relatively lower energy and material requirements. Second is the non-recyclability nature of tissue paper. Because the tissue paper is the last use of fibre, using RWP as an input would be preferable over using VP. The environmental profile of the tissue products both from RWP and VP can be improved if the following conditions are considered by the company. First, the company should consider implementing a cogeneration unit to simultaneously generate both useful heat and electricity. Second, it may consider changing the VP mix, in order to avoid the emissions associated with long distance transpiration effort. Third, there is the option of using sludge as fuel, which would reduce the total fossil fuel requirement.     

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.

     

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.

     

A life cycle carbon dioxide inventory of the Million Trees Los Angeles program

Purpose

This study seeks to answer the question, “Will the Million Trees LA (Million Trees Los Angeles, MTLA) program be a carbon dioxide (CO₂) sink or source?” Because there has never been a full accounting of CO₂ emissions, it is unclear if urban tree planting initiatives (TPIs) are likely to be effective means for reaching local reduction targets.

Methods

Using surveys, interviews, field sampling, and computer simulation of tree growth and survival over a 40-year time period, we developed the first process-based life cycle inventory of CO₂ for a large TPI. CO₂ emissions and reductions from storage and avoided emissions from energy savings were simulated for 91,786 trees planted from 2006 to 2010, of which only 30,813 (33.6 %) were estimated to survive.

Results and discussion

The MTLA program was estimated to release 17,048 and 66,360 t of fossil and biogenic CO₂ over the 40-year period, respectively. The total amount emitted (83,408 t) was slightly more than the ?77,942 t CO₂ that trees were projected to store in their biomass. The MTLA program will be a CO₂ sink if projected 40-year-avoided fossil fuel CO₂ emissions from energy savings (?101,679 t) and biopower (?1,939 t) are realized. The largest sources of CO₂ emissions were mulch decomposition (65.1 %), wood combustion (14.5 %), and irrigation water (9.7 %).

Conclusions

Although trees planted by the MTLA program are likely to be a net CO₂ sink, there is ample opportunity to reduce emissions. Examples of these opportunities include selecting drought-tolerant trees and utilizing wood residue to generate electricity rather than producing mulch.     

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 Analysis of Greenhouse Gas and PM<Subscript>2.5</Subscript> Emissions from Restaurant Waste Oil Used for Biodiesel Production in China

Waste cooking oil (WCO) can serve as a feedstock for producing biodiesel, which would not only address food security and waste disposal but also has the potential to reduce emissions of greenhouse gas (GHG) and particulate matter of 2.5 μm or smaller (PM_2.5). In this study, we assessed restaurant waste oil (RWO) availability in China and conducted life cycle analysis (LCA) of GHG and PM_2.5 emissions of RWO-based biodiesel using the GREET model. The results showed that the amount of RWO in China varies between 0.56 and 1.67 million tons in 2013 and between 0.54 and 1.63 million tons in 2014. Life cycle analysis estimated reduction of GHG and PM_2.5 emissions through the use of RWO-based rather than petroleum-based biodiesel of 82 kg CO₂-Eq. (90 %) and 0.92 g PM_2.5 (46 %) respectively per 100 km driven by busses in 2014 in Shanghai, China. Given the total amount of RWO available in 2014 in China, the potential mitigated annual GHG emission ranges, in China, are 1.51 ～ 4.52 × 10⁶ tons of CO₂-eq and 16.94 ～ 50.83 tons of PM_2.5.     

Life cycle assessment of commodity chemical production from forest residue via fast pyrolysis

Purpose

This life cycle assessment evaluates and quantifies the environmental impacts of renewable chemical production from forest residue via fast pyrolysis with hydrotreating/fluidized catalytic cracking (FCC) pathway.

Methods

The assessment input data are taken from Aspen Plus and greenhouse gases, regulated emissions, and energy use in transportation (GREET) model. The SimaPro 7.3 software is employed to evaluate the environmental impacts.

Results and discussion

The results indicate that the net fossil energy input is 34.8 MJ to produce 1 kg of chemicals, and the net global warming potential (GWP) is ?0.53 kg CO₂ eq. per kg chemicals produced under the proposed chemical production pathway. Sensitivity analysis indicates that bio-oil yields and chemical yields play the most important roles in the greenhouse gas footprints.

Conclusions

Fossil energy consumption and greenhouse gas (GHG) emissions can be reduced if commodity chemicals are produced via forest residue fast pyrolysis with hydrotreating/FCC pathway in place of conventional petroleum-based production pathways.