Implementing an appropriate metric for the assessment of greenhouse gas emissions from livestock production: A national case study

Livestock farming is of major economic relevance but also severely contributes to environmental impacts, especially greenhouse gas (GHG) emissions such as methane (CH₄; particularly from ruminant production) and nitrous oxide (N₂O; mainly from manure management and soil cultivated for feed production). In this study, we analyse the impact of GHG emissions from Austrian livestock production, using two metrics: a) the commonly used global warming potential (GWP) over 100 years (GWP₁₀₀ in CO₂-equivalents, CO₂-e), and b) the recently introduced metric GWP*, which describes additional warming as a function of the timeline of short-lived GHG emissions (unit CO₂ warming equivalents, CO₂-we). We first compiled the sectoral (i.e. only direct emissions without upstream processes) GWP₁₀₀ for different livestock categories with a focus on dairy cattle, beef cattle and pigs in Austria between 1990 and 2019. We also estimated product-related (i.e. per kg carcass weight or per litre of milk) GWP₁₀₀ values, including upstream processes. We then calculated the corresponding GWP* metrics, both sectoral and product-related, and compared them with the GWP₁₀₀ values. Decreasing livestock numbers and improved production efficiency were found to result in strong sectoral emission reductions from dairy production (–32 % of GWP₁₀₀ from 1990 to 2019) and from pigs (–32 % CO₂-e). This contrasts with low reductions from other livestock categories and even increases for cattle other than dairy cows (+3 % CO₂-e), mainly due to rising suckler cow numbers. Allocated results per kg milk and kg body mass show quite similar results. Using the GWP* metric, the climate impacts of Austrian livestock production are less severe. When assuming constant management and emission intensity over a period of at least 20 years, the CO₂-we (GWP*) is almost 50 % less than CO₂-e (GWP₁₀₀) per kg Austrian raw milk due to the different impacts of the short-lived CH₄. A similar trend applies to an average cattle carcass (-40 % warming impact). The emission reductions of the shrinking Austrian livestock population represent an important contribution to a climate-neutral agriculture: The CH₄ reductions of livestock production during the past 20 years reduce the current total Austrian CO₂-we by 16 %. Continuous CH₄ reduction, as we show it here for Austrian livestock, is an effective option to tackle the climate crisis in the short term. It shall be stressed that a relatively low GWP* should not be interpreted as a concession for further CH₄ emissions but as an actual reduction of (additional) warming.     

Including albedo in time‐dependent LCA of bioenergy

Albedo change during feedstock production can substantially alter the life cycle climate impact of bioenergy. Life cycle assessment (LCA) studies have compared the effects of albedo and greenhouse gases (GHGs) based on global warming potential (GWP). However, using GWP leads to unequal weighting of climate forcers that act on different timescales. In this study, albedo was included in the time‐dependent LCA, which accounts for the timing of emissions and their impacts. We employed field‐measured albedo and life cycle emissions data along with time‐dependent models of radiative transfer, biogenic carbon fluxes and nitrous oxide emissions from soil. Climate impacts were expressed as global mean surface temperature change over time (?T) and as GWP. The bioenergy system analysed was heat and power production from short‐rotation willow grown on former fallow land in Sweden. We found a net cooling effect in terms of ?T per hectare (?3.8 × 10^–11 K in year 100) and GWP₁₀₀ per MJ fuel (?12.2 g CO₂e), as a result of soil carbon sequestration via high inputs of carbon from willow roots and litter. Albedo was higher under willow than fallow, contributing to the cooling effect and accounting for 34% of GWP₁₀₀, 36% of ?T in year 50 and 6% of ?T in year 100. Albedo dominated the short‐term temperature response (10–20 years) but became, in relative terms, less important over time, owing to accumulation of soil carbon under sustained production and the longer perturbation lifetime of GHGs. The timing of impacts was explicit with ?T, which improves the relevance of LCA results to climate targets. Our method can be used to quantify the first‐order radiative effect of albedo change on the global climate and relate it to the climate impact of GHG emissions in LCA of bioenergy, alternative energy sources or land uses.     

Climate mitigation by dairy intensification depends on intensive use of spared grassland

Milk and beef production cause 9% of global greenhouse gas (GHG) emissions. Previous life cycle assessment (LCA) studies have shown that dairy intensification reduces the carbon footprint of milk by increasing animal productivity and feed conversion efficiency. None of these studies simultaneously evaluated indirect GHG effects incurred via teleconnections with expansion of feed crop production and replacement suckler‐beef production. We applied consequential LCA to incorporate these effects into GHG mitigation calculations for intensification scenarios among grazing‐based dairy farms in an industrialized country (UK), in which milk production shifts from average to intensive farm typologies, involving higher milk yields per cow and more maize and concentrate feed in cattle diets. Attributional LCA indicated a reduction of up to 0.10 kg CO₂e kg^?1 milk following intensification, reflecting improved feed conversion efficiency. However, consequential LCA indicated that land use change associated with increased demand for maize and concentrate feed, plus additional suckler‐beef production to replace reduced dairy‐beef output, significantly increased GHG emissions following intensification. International displacement of replacement suckler‐beef production to the “global beef frontier” in Brazil resulted in small GHG savings for the UK GHG inventory, but contributed to a net increase in international GHG emissions equivalent to 0.63 kg CO₂e kg^?1 milk. Use of spared dairy grassland for intensive beef production can lead to net GHG mitigation by replacing extensive beef production, enabling afforestation on larger areas of lower quality grassland, or by avoiding expansion of international (Brazilian) beef production. We recommend that LCA boundaries are expanded when evaluating livestock intensification pathways, to avoid potentially misleading conclusions being drawn from “snapshot” carbon footprints. We conclude that dairy intensification in industrialized countries can lead to significant international carbon leakage, and only achieves GHG mitigation when spared dairy grassland is used to intensify beef production, freeing up larger areas for afforestation.     

The potential to mitigate global warming with no-tillage management is only realized when practised in the long term

No‐tillage (NT) management has been promoted as a practice capable of offsetting greenhouse gas (GHG) emissions because of its ability to sequester carbon in soils. However, true mitigation is only possible if the overall impact of NT adoption reduces the net global warming potential (GWP) determined by fluxes of the three major biogenic GHGs (i.e. CO₂, N₂O, and CH₄). We compiled all available data of soil‐derived GHG emission comparisons between conventional tilled (CT) and NT systems for humid and dry temperate climates. Newly converted NT systems increase GWP relative to CT practices, in both humid and dry climate regimes, and longer‐term adoption (>10 years) only significantly reduces GWP in humid climates. Mean cumulative GWP over a 20‐year period is also reduced under continuous NT in dry areas, but with a high degree of uncertainty. Emissions of N₂O drive much of the trend in net GWP, suggesting improved nitrogen management is essential to realize the full benefit from carbon storage in the soil for purposes of global warming mitigation. Our results indicate a strong time dependency in the GHG mitigation potential of NT agriculture, demonstrating that GHG mitigation by adoption of NT is much more variable and complex than previously considered, and policy plans to reduce global warming through this land management practice need further scrutiny to ensure success.     

Progress in the studies on the greenhouse gas emissions from reservoirs

The green credentials of hydroelectricity in terms of greenhouse-gas (GHG) emissions have been tarnished with the finding of the researches on GHG emissions from hydroelectric reservoirs in the last two decades. Substantial amounts of GHGs release from the tropical reservoirs, especially methane (CH₄) from Brazil’s Amazonian areas. CH₄ contributes strongly to climate change because it has a global warming potential (GWP) 24 times higher than carbon dioxide (CO₂) on a per molecule basis over a 100-year time horizon. GHGs may emit from reservoirs through four different pathways to the atmosphere: (1) diffusive flux at the reservoir surface, (2) gas bubble flux in the shallow zones of a reservoir, (3) water degassing flux at the outlet of the powerhouse downstream of turbines and spillways, and (4) flux across the air–water interface in the rivers downstream of the dams. This paper reviewed the productions and emissions of CH₄, CO₂, and N₂O in reservoirs, and the environmental variables influencing CH₄ and CO₂ emissions were also summarized. Moreover, the paper combined with the progress of GHG emissions from Three Gorges Reservoir and proposed three crucial problems to be resolved on GHG emissions from reservoirs at present, which would be benefit to estimate the total GHG emissions from Three Gorges Reservoir accurately.     

Effect of improved nitrogen management on greenhouse gas emissions from intensive dairy systems in the Netherlands

Dairy systems in Europe contribute to the emissions of the greenhouse gases (GHGs) nitrous oxide (N₂O), methane (CH₄) and carbon dioxide (CO₂). In this paper, the effects of improved nitrogen (N) management on GHG emissions from Dutch dairy farms are determined. The GHG emissions are calculated using the panel on climate change (IPCC) methodology for the Netherlands, an updated and refined IPCC methodology, and a full accounting approach. The changes in dairy farming over the last 20 years, and the consequences for N management are described using detailed farm‐level data, collected in 1985, 1997 and 2002. The selected years represent distinct stages in the implementation of N policies. The changes in N management have reduced the GHG emissions. A reduction of the N surplus per kilogram milk with 1 g N reduced the GHG emissions per kilogram milk with approximately 29 g CO₂‐equivalents. The reduction of the N surpluses was mainly brought about by reduced fertilizer use and reduced grazing time. The use of updated and refined emission factors resulted in higher CH₄ emissions and lower N₂O emissions. On average, the overall emission was 36% higher with the refined method. Full accounting, including all direct and indirect emissions of CH₄, N₂O and CO₂, increased the emission with 36% compared with the refined IPCC methodology. We conclude that the N surplus at farm level is a useful indicator of GHG emissions. A full accounting system as presented in this study may effectively enable farmers to address the issue of emissions of GHGs in their operational management decisions. Both approaches serve their own specific objectives: full accounting at the farm level to explore mitigation options, and the IPCC methods to report changes in GHG emissions at the national level.     

LIFE BEEF CARBON: a common framework for quantifying grass and corn based beef farms’ carbon footprints

Europe’s roadmap to a low-carbon economy aims to cut greenhouse gas (GHG) emissions 80% below 1990 levels by 2050. Beef production is an important source of GHG emissions and is expected to increase as the world population grows. LIFE BEEF CARBON is a voluntary European initiative that aims to reduce GHG emissions per unit of beef (carbon footprint) by 15% over a 10-year period on 2172 farms in four large beef-producing countries. Changes in farms beef carbon footprint are normally estimated via simulation modelling, but the methods current models apply differ. Thus, our initial goal was to develop a common modelling framework to estimate beef farms carbon footprint. The framework was developed for a diverse set of Western Europe farms located in Ireland, Spain, Italy and France. Whole farm and life cycle assessment (LCA) models were selected to quantify emissions for the different production contexts and harmonized. Carbon Audit was chosen for Ireland, Bovid-CO₂ for Spain and CAP’2ER for France and Italy. All models were tested using 20 case study farms, that is, 5 per country and quantified GHG emissions associated with on-farm live weight gain. The comparison showed the ranking of beef systems gross carbon footprint was consistent across the three models. Suckler to weaning or store systems generally had the highest carbon footprint followed by suckler to beef systems and fattening beef systems. When applied to the same farm, Carbon Audit’s footprint estimates were slightly lower than CAP’2ER, but marginally higher than Bovid-CO₂. These differences occurred because the models were adapted to a specific region’s production circumstances, which meant their emission factors for key sources; that is, methane from enteric fermentation and GHG emissions from concentrates were less accurate when used outside their target region. Thus, for the common modelling framework, region-specific LCA models were chosen to estimate beef carbon footprints instead of a single generic model. Additionally, the Carbon Audit and Bovid-CO₂ models were updated to include carbon removal by soil and other environmental metrics included in CAP’2ER, for example, acidification. This allows all models to assess the effect carbon mitigation strategies have on other potential pollutants. Several options were identified to reduce beef farms carbon footprint, for example, improving genetic merit. These options were assessed for beef systems, and a mitigation plan was created by each nation. The cumulative mitigation effect of the LIFE BEEF CARBON plan was estimated to exceed the projects reduction target (−15%).     

Assessment of urgent impacts of greenhouse gas emissions—the climate tipping potential (CTP)

Purpose

The impact of anthropogenic greenhouse gas (GHG) emissions on climate change receives much focus today. This impact is however often considered only in terms of global warming potential (GWP), which does not take into account the need for staying below climatic target levels, in order to avoid passing critical climate tipping points. Some suggestions to include a target level in climate change impact assessment have been made, but with the consequence of disregarding impacts beyond that target level. The aim of this paper is to introduce the climate tipping impact category, which represents the climate tipping potential (CTP) of GHG emissions relative to a climatic target level. The climate tipping impact category should be seen as complementary to the global warming impact category.

Methods

The CTP of a GHG emission is expressed as the emission’s impact divided by the ‘capacity’ of the atmosphere for absorbing the impact without exceeding the target level. The GHG emission impact is determined as its cumulative contribution to increase the total atmospheric GHG concentration (expressed in CO₂ equivalents) from the emission time to the point in time where the target level is expected to be reached, the target time.

Results and discussion

The CTP of all the assessed GHGs increases as the emission time approaches the target time, reflecting the rapid decrease in remaining atmospheric capacity and thus the increasing potential impact of the GHG emission. The CTP of a GHG depends on the properties of the GHG as well as on the chosen climatic target level and background scenario for atmospheric GHG concentration development. In order to enable direct application in life cycle assessment (LCA), CTP characterisation factors are presented for the three main anthropogenic GHGs, CO₂, CH₄ and N₂O.

Conclusions

The CTP metric distinguishes different GHG emission impacts in terms of their contribution to exceeding a short-term target and highlights their increasing importance when approaching a climatic target level, reflecting the increasing urgency of avoiding further GHG emissions in order to stay below the target level. Inclusion of the climate tipping impact category for assessing climate change impacts in LCA, complimentary to the global warming impact category which shall still represent the long-term climate change impacts, is considered to improve the value of LCA as a tool for decision support for climate change mitigation.     

Life cycle analysis of biochemical cellulosic ethanol under multiple scenarios

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

Life cycle assessment of California unsweetened almond milk

Purpose

Plant-based alternatives to dairy milk have grown in popularity over the last decade. Almond milk comprises the largest share of plant-based milk in the US market and, as with so many food products, stakeholders in the supply chain are increasingly interested in understanding the environmental impacts of its production, particularly its carbon footprint and water consumption. This study undertakes a life cycle assessment (LCA) of a California unsweetened almond milk.

Methods

The scope of this LCA includes the production of almond milk in primary packaging at the factory gate. California produces all US almonds, which are grown under irrigated conditions. Spatially resolved modeling of almond cultivation and primary data collection from one almond milk supply chain were used to develop the LCA model. While the environmental indicators of greatest interest are global warming potential (GWP) and freshwater consumption (FWC), additional impact categories from US EPA’s TRACI assessment method are also calculated. Co-products are accounted for using economic allocation, but mass-based allocation and displacement are also tested to understand the effect of co-product allocation choices on results.

Results and discussion

The GWP and FWC of one 48 oz. (1.42 L) bottle of unsweetened almond milk are 0.71 kg CO₂e and 175 kg of water. A total of 0.39 kg CO₂e (or 55%) of the GWP is attributable to the almond milk, with the remainder attributable to packaging. Almond cultivation alone is responsible for 95% of the FWC (167 kg H₂O), because of irrigation water demand. Total primary energy consumption (TPE) is estimated at 14.8 MJ. The 48 oz. (1.42 L) PET bottle containing the almond milk is the single largest contributor to TPE (42%) and GWP (35%). Using recycled PET instead of virgin PET for the bottle considerably reduces all impact indicators except for eutrophication potential.

Conclusions

For the supply chain studied here, packaging choices provide the most immediate opportunities for reducing impacts related to GWP and TPE, but would not result in a significant reduction in FWC because irrigation water for almond cultivation is the dominant consumer. To provide context for interpretation, average US dairy milk appears to have about 4.5 times the GWP and 1.8 times the FWC of the studied almond milk on a volumetric basis.

     

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.     

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

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

Carbon and nitrogen dynamics in bioenergy ecosystems: 2. Potential greenhouse gas emissions and global warming intensity in the conterminous United States

This study estimated the potential emissions of greenhouse gases (GHG) from bioenergy ecosystems with a biogeochemical model AgTEM, assuming maize (Zea mays L.), switchgrass (Panicum virgatum L.), and Miscanthus (Miscanthus × giganteus) will be grown on the current maize‐producing areas in the conterminous United States. We found that the maize ecosystem acts as a mild net carbon source while cellulosic ecosystems (i.e., switchgrass and Miscanthus) act as mild sinks. Nitrogen fertilizer use is an important factor affecting biomass production and N₂O emissions, especially in the maize ecosystem. To maintain high biomass productivity, the maize ecosystem emits much more GHG, including CO₂ and N₂O, than switchgrass and Miscanthus ecosystems, when high‐rate nitrogen fertilizers are applied. For maize, the global warming potential (GWP) amounts to 1–2 Mg CO₂eq ha^?1 yr^?1, with a dominant contribution of over 90% from N₂O emissions. Cellulosic crops contribute to the GWP of less than 0.3 Mg CO₂eq ha^?1 yr^?1. Among all three bioenergy crops, Miscanthus is the most biofuel productive and the least GHG intensive at a given cropland. Regional model simulations suggested that substituting Miscanthus for maize to produce biofuel could potentially save land and reduce GHG emissions.     

Environmental footprinting of hospitals: Organizational life cycle assessment of a Canadian hospital

Healthcare is a critical and complex service sector with direct and indirect greenhouse gas (GHG) emissions amounting to 5%–10% of the national total in developed economies like Canada and the United States. Along with a growing, albeit sporadic, set of life cycle assessment (LCA) (and “carbon footprinting”) studies of specific medical products and procedures, there is growing interest in “environmental footprinting” of hospitals. In this article, we advance this rapidly evolving area through a comprehensive organizational LCA of a 40-bed hospital in British Columbia, Canada, in its 2019 fiscal year. Our results indicate that the total environmental footprint of the hospital includes, among other things, global warming potential of 3500–5000 t CO₂ eq. (with 95% confidence). “Hotspots” in this footprint are attributable to energy and water use (and wastewater released), releases of anesthetic gases (which are potent GHGs), and the upstream production of the thousands of materials, chemicals, pharmaceuticals, and other products used in the hospital. The generalizability and comparability of these results are limited by inconsistencies across the few environmental footprinting studies of hospitals conducted to date. Nonetheless, our novel methodological approach, in which we compiled new LCA data for 200 goods and services used in healthcare—strategically selected to statistically represent the 2927 unique products in the hospital's “supply-chains”—has broad applicability in healthcare and beyond.     

Net greenhouse gas balance in response to nitrogen enrichment: perspectives from a coupled biogeochemical model

Increasing reactive nitrogen (N) input has been recognized as one of the important factors influencing climate system through affecting the uptake and emission of greenhouse gases (GHG). However, the magnitude and spatiotemporal variations of N‐induced GHG fluxes at regional and global scales remain far from certain. Here we selected China as an example, and used a coupled biogeochemical model in conjunction with spatially explicit data sets (including climate, atmospheric CO₂, O₃, N deposition, land use, and land cover changes, and N fertilizer application) to simulate the concurrent impacts of increasing atmospheric and fertilized N inputs on balance of three major GHGs (CO₂, CH₄, and N₂O). Our simulations showed that these two N enrichment sources in China decreased global warming potential (GWP) through stimulating CO₂ sink and suppressing CH₄ emission. However, direct N₂O emission was estimated to offset 39% of N‐induced carbon (C) benefit, with a net GWP of three GHGs averaging ?376.3 ± 146.4 Tg CO₂ eq yr^?1 (the standard deviation is interannual variability of GWP) during 2000–2008. The chemical N fertilizer uses were estimated to increase GWP by 45.6 ± 34.3 Tg CO₂ eq yr^?1 in the same period, and C sink was offset by 136%. The largest C sink offset ratio due to increasing N input was found in Southeast and Central mainland of China, where rapid industrial development and intensively managed crop system are located. Although exposed to the rapidly increasing N deposition, most of the natural vegetation covers were still showing decreasing GWP. However, due to extensive overuse of N fertilizer, China's cropland was found to show the least negative GWP, or even positive GWP in recent decade. From both scientific and policy perspectives, it is essential to incorporate multiple GHGs into a coupled biogeochemical framework for fully assessing N impacts on climate changes.     

Including CO2 implications of land occupation in LCAs—method and example for livestock products

Purpose

Until recently, life cycle assessments (LCAs) have only addressed the direct greenhouse gas emissions along a process chain, but ignored the CO₂ emissions of land-use. However, for agricultural products, these emissions can be substantial. Here, we present a new methodology for including the implications of land occupation for CO₂ emissions to realistically reflect the consequences of consumers?? decisions.

Method

In principle, one can distinguish five different approaches of addressing the CO₂ consequences of land occupation: (1) assuming constant land cover, (2) land-use change related to additional production of the product under consideration, (3) historic land-use change, assuming historical relations between existing area and area expansion (4) land-use change related to less production of the product under consideration (??missed potential carbon sink?? of land occupation), and (5) an approach of integrating land conversion emissions and delayed uptake due to land occupation. Approach (4) is presented in this paper, using LCA data on land occupation, and carbon dynamics from the IMAGE model. Typically, if less production occurs, agricultural land will be abandoned, leading to a carbon sink when vegetation is regrowing. This carbon sink, which does not occur if the product would still be consumed, is thus attributed to the product as ??missed potential carbon sink??, to reflect the CO₂ implications of land occupations.

Results

We analyze the missed potential carbon sink by relating land occupation data from LCA studies to the potential carbon sink as calculated by an Integrated Global Assessment Model and its process-based, spatially explicit carbon cycle model. Thereby, we account for regional differences, heterogeneity in land-use, and different time horizons. Example calculations for several livestock products show that the CO₂ consequences of land occupation can be in the same order of magnitude as the other process related greenhouse gas emissions of the LCA, and depend largely on the production system. The highest CO₂ implications of land occupation are calculated for beef and lamb, with beef production in Brazil having a missed potential carbon sink more than twice as high as the other GHG emissions.

Conclusions

Given the significant contribution of land occupation to the total GHG balance of agricultural products, they need to be included in life cycle assessments in a realistic way. The new methodology presented here reflects the consequences of producing or not producing a certain commodity, and thereby it is suited to inform consumers fully about the consequences of their choices.     

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.     

How does co-product handling affect the carbon footprint of milk? Case study of milk production in New Zealand and Sweden

Purpose  

This paper investigates different methodologies of handling co-products in life cycle assessment (LCA) or carbon footprint (CF) studies. Co-product handling can have a significant effect on final LCA/CF results, and although there are guidelines on the preferred order for different methods for handling co-products, no agreed understanding on applicable methods is available. In the present study, the greenhouse gases (GHG) associated with the production of 1 kg of energy-corrected milk (ECM) at farm gate is investigated considering co-product handling.     

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

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

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.