A multi‐criteria based review of models that predict environmental impacts of land use‐change for perennial energy crops on water,carbon and nitrogen cycling

Reduction in energy sector greenhouse gas GHG emissions is a key aim of European Commission plans to expand cultivation of bioenergy crops. Since agriculture makes up 10–12% of anthropogenic GHG emissions, impacts of land‐use change must be considered, which requires detailed understanding of specific changes to agroecosystems. The greenhouse gas (GHG) balance of perennials may differ significantly from the previous ecosystem. Net change in GHG emissions with land‐use change for bioenergy may exceed avoided fossil fuel emissions, meaning that actual GHG mitigation benefits are variable. Carbon (C) and nitrogen (N) cycling are complex interlinked systems, and a change in land management may affect both differently at different sites, depending on other variables. Change in evapotranspiration with land‐use change may also have significant environmental or water resource impacts at some locations. This article derives a multi‐criteria based decision analysis approach to objectively identify the most appropriate assessment method of the environmental impacts of land‐use change for perennial energy crops. Based on a literature review and conceptual model in support of this approach, the potential impacts of land‐use change for perennial energy crops on GHG emissions and evapotranspiration were identified, as well as likely controlling variables. These findings were used to structure the decision problem and to outline model requirements. A process‐based model representing the complete agroecosystem was identified as the best predictive tool, where adequate data are available. Nineteen models were assessed according to suitability criteria, to identify current model capability, based on the conceptual model, and explicit representation of processes at appropriate resolution. FASSET, ECOSSE, ANIMO, DNDC, DayCent, Expert‐N, Ecosys, WNMM and CERES‐NOE were identified as appropriate models, with factors such as crop, location and data availability dictating the final decision for a given project. A database to inform such decisions is included.     

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

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

More or Better? A Model for Changes in Household Greenhouse Gas Emissions due to Higher Income

Households exert an important influence on total greenhouse gas (GHG) emissions. Therefore, their consumption behavior is of interest in evaluations of climate policy options and projections of future emission paths. While most evaluations of household consumption and its emissions are based on expenditure only, we use a household consumption model based on functional units (e.g., kg food, person kilometers, living square meters). The goal of this article is to assess changes in consumption with increasing affluence level of households and to compare the allocation of GHG emissions to monetary versus functional units. We find that (1) the model based on functional units provides good bottom-up estimates for greenhouse emissions of Swiss households; (2) quality (price per functional unit) increases with income for many consumption categories, and therefore using functional instead of monetary units leads to a lower increase of greenhouse gas emissions with income; (3) the relevance of GHG emissions from goods and mobility will increase. We conclude that using household models based on monetary units only overestimates the impact of marginal consumption and neglects the potential of decoupling income and environmental impact by consuming better instead of more. For sustainable consumption, research and policy should aim at preventing goods of higher quality from having higher environmental impact in order to benefit from the increasing quality orientation with rising income.     

Environmental assessment of urban mobility: Combining life cycle assessment with land-use and transport interaction modelling—Application to Lyon (France)

In France, greenhouse gas (GHG) emissions from transport have grown steadily since 1950 and transport is now the main source of emissions. Despite technological improvements, urban sprawl increases the environmental stress due to car use. This study evaluates urban mobility through assessments of the transport system and travel habits, by applying life cycle assessment methods to the results of mobility simulations that were produced by a Land Use and Transport Interactions (LUTI) model. The environmental impacts of four life cycle phases of urban mobility in the Lyon area (exhausts, fuel processing, infrastructure and vehicle life cycle) were estimated through nine indicators (global warming potential, particulate matter emissions, photochemical oxidant emissions, terrestrial acidification, fossil resource depletion, metal depletion, non-renewable energy use, renewable energy use and land occupancy). GHG emissions were estimated to be 3.02 kg CO₂-eq inhabitant⁻¹ day⁻¹, strongly linked to car use, and indirect impacts represented 21% of GHG emissions, which is consistent with previous studies. Combining life cycle assessment (LCA) with a LUTI model allows changes in the vehicle mix and fuel sources combined with demographic shifts to be assessed, and provides environmental perspectives for transport policy makers and urban planners. It can also provide detailed analysis, by allowing levels of emissions that are generated by different categories of households to be differentiated, according to their revenue and location. Public policies can then focus more accurately on the emitters and be assessed from both an environmental and social point of view.     

Implications of land class and environmental factors on life cycle GHG emissions of Miscanthus as a bioenergy feedstock

Replacement of fossil fuels with sustainably produced biomass crops for energy purposes has the potential to make progress in addressing climate change concerns, nonrenewable resource use, and energy security. The perennial grass Miscanthus is a dedicated energy crop candidate being field tested in Ontario, Canada, and elsewhere. Miscanthus could potentially be grown in areas of the province that differ substantially in terms of agricultural land class, environmental factors and current land use. These differences could significantly affect Miscanthus yields, input requirements, production practices, and the types of crops being displaced by Miscanthus establishment. This study assesses implications on life cycle greenhouse gas (GHG) emissions of these differences through evaluating five Miscanthus production scenarios within the Ontario context. Emissions associated with electricity generation with Miscanthus pellets in a hypothetically retrofitted coal generating station are examined. Indirect land use change impacts are not quantified but are discussed. The net life cycle emissions for Miscanthus production varied greatly among scenarios (?90–170 kg CO₂eq per oven dry tonne of Miscanthus bales at the farm gate). In some cases, the carbon stock dynamics of the agricultural system offset the combined emissions of all other life cycle stages (i.e., production, harvest, transport, and processing of biomass). Yield and soil C of the displaced agricultural systems are key parameters affecting emissions. The systems with the highest potential to provide reductions in GHG emissions are those with high yields, or systems established on land with low soil carbon. All scenarios have substantially lower life cycle emissions (?20–190 g CO₂eq kWh^?1) compared with coal‐generated electricity (1130 g CO₂eq kWh^?1). Policy development should consider the implication of land class, environmental factors, and current land use on Miscanthus production.     

Challenges in the design of indicators for assessing the impact of the Scotland Rural Development Programme 2007–2013 on climate change mitigation

This paper addresses the use of impact indicators with respect to climate change in the 2007–2013 Rural Development Programme (RDP) of the European Union, with particular reference to the Scotland Rural Development Programme (SRDP). It concludes that the policy context has highlighted the need for the rural land use sector to respond to climate change but that the associated Common Monitoring and Evaluation Framework (CMEF) did not develop suitable indicators to assess the impact of SDRP measures on GHG emission mitigation. It suggests improved impact indicators based on the relationship between rural land use and greenhouse gas (GHG) emissions: first, an indicator based on net GHG emissions per holding; and a second based on net GHG emissions per unit volume of output. The paper points out the challenges in measuring land-based emissions accurately. It further proposes screening of RDP measures to ensure that climate change mitigation impacts are properly appraised. It is recognised that climate change policy in relation to rural land use is still at an early stage of development but greater sophistication of policy instrument design and evaluation will be required if the RDP is to contribute significantly to climate change policy objectives.     

Localising livestock protein feed production and the impact on land use and greenhouse gas emissions

Livestock farmers in Sweden usually grow feed grains for livestock but import protein feed from outside Sweden. Aside from the economic implications, some environmental issues are associated with this practice. We used life cycle assessment to evaluate the impact of local protein feed production on land use and greenhouse gas emissions, compared with the use of imported protein feed, for pig meat and dairy milk produced in Sweden. Our results showed that local production reduced greenhouse gas emissions by 4.5% and 12%, respectively, for pigs and dairy cows. Land use for feed production in Sweden increased by 11% for pigs and 25% for dairy cows, but total land use decreased for pig production and increased for dairy milk production. Increased protein feed cultivation in Sweden decreased inputs needed for animal production and improved some ecological processes (e.g. nutrient recycling) of the farm systems. However, the differences in results between scenarios are relatively small and influenced to an extent by methodological choices such as co-product allocation. Moreover, it was difficult to assess the contribution of greenhouse emissions from land use change. The available accounting methods we applied did not adequately account for the potential land use changes and in some cases provided conflicting results. We conclude that local protein feed production presents an opportunity to reduce greenhouse gas emissions but at a cost of increasing land occupation in Sweden for feed production.     

Global environmental costs of China's thirst for milk

China has an ever‐increasing thirst for milk, with a predicted 3.2‐fold increase in demand by 2050 compared to the production level in 2010. What are the environmental implications of meeting this demand, and what is the preferred pathway? We addressed these questions by using a nexus approach, to examine the interdependencies of increasing milk consumption in China by 2050 and its global impacts, under different scenarios of domestic milk production and importation. Meeting China's milk demand in a business as usual scenario will increase global dairy‐related (China and the leading milk exporting regions) greenhouse gas (GHG) emissions by 35% (from 565 to 764 Tg CO_2eq) and land use for dairy feed production by 32% (from 84 to 111 million ha) compared to 2010, while reactive nitrogen losses from the dairy sector will increase by 48% (from 3.6 to 5.4 Tg nitrogen). Producing all additional milk in China with current technology will greatly increase animal feed import; from 1.9 to 8.5 Tg for concentrates and from 1.0 to 6.2 Tg for forage (alfalfa). In addition, it will increase domestic dairy related GHG emissions by 2.2 times compared to 2010 levels. Importing the extra milk will transfer the environmental burden from China to milk exporting countries; current dairy exporting countries may be unable to produce all additional milk due to physical limitations or environmental preferences/legislation. For example, the farmland area for cattle‐feed production in New Zealand would have to increase by more than 57% (1.3 million ha) and that in Europe by more than 39% (15 million ha), while GHG emissions and nitrogen losses would increase roughly proportionally with the increase of farmland in both regions. We propose that a more sustainable dairy future will rely on high milk demanding regions (such as China) improving their domestic milk and feed production efficiencies up to the level of leading milk producing countries. This will decrease the global dairy related GHG emissions and land use by 12% (90 Tg CO_2eq reduction) and 30% (34 million ha land reduction) compared to the business as usual scenario, respectively. However, this still represents an increase in total GHG emissions of 19% whereas land use will decrease by 8% when compared with 2010 levels, respectively.     

The Impacts of Dietary Change on Greenhouse Gas Emissions,Land Use,Water Use,and Health: A Systematic Review

Food production is a major driver of greenhouse gas (GHG) emissions, water and land use, and dietary risk factors are contributors to non-communicable diseases. Shifts in dietary patterns can therefore potentially provide benefits for both the environment and health. However, there is uncertainty about the magnitude of these impacts, and the dietary changes necessary to achieve them. We systematically review the evidence on changes in GHG emissions, land use, and water use, from shifting current dietary intakes to environmentally sustainable dietary patterns. We find 14 common sustainable dietary patterns across reviewed studies, with reductions as high as 70–80% of GHG emissions and land use, and 50% of water use (with medians of about 20–30% for these indicators across all studies) possible by adopting sustainable dietary patterns. Reductions in environmental footprints were generally proportional to the magnitude of animal-based food restriction. Dietary shifts also yielded modest benefits in all-cause mortality risk. Our review reveals that environmental and health benefits are possible by shifting current Western diets to a variety of more sustainable dietary patterns.     

Greenhouse gas emissions and the technical efficiency of dairy farmers

Agriculture in Scotland is facing immense challenges for the future. Scottish policy now promotes sustainable economic growth, which to many implies both a growth in resource use and the requirement to meet targets for reducing greenhouse gas emissions. Attempts to increase economic gains can be in conflict with environmental aims and the question arises how both objectives can be met simultaneously.This paper examines the relationship between the technical and environmental efficiency of dairy farms in Scotland with respect to greenhouse gas emissions. It estimates the technical efficiency of a sample of dairy farms based on survey data, applying a number of approaches based on the non-parametric Data Envelopment Analysis (DEA) method. The farms’ greenhouse gas emissions are calculated using a variety of sources and were used to estimate environmental efficiency. This paper finds that, within the study sample, farms which are more technically efficient, are bigger or have higher yields are also more efficient in their emissions of GHG emissions.These results suggest that the potential exists for, Scottish dairying to improve its competitiveness and lower greenhouse gas emissions by increasing efficiency, though the extent of the environmental benefits achieved largely depends on how efficiency is increased.     

The True Cost of Greenhouse Gas Emissions: Analysis of 1,000 Global Companies

This study elucidated the shadow price of greenhouse gas (GHG) emissions for 1,024 international companies worldwide that were surveyed from 15 industries in 37 major countries. Our results indicate that the shadow price of GHG at the firm level is much higher than indicated in previous studies. The higher shadow price was found in this study as a result of the use of Scope 3 GHG emissions data. The results of this research indicate that a firm would carry a high cost of GHG emissions if Scope 3 GHG emissions were the focus of the discussion of corporate social responsibility. In addition, such shadow prices were determined to differ substantially among countries, among sectors, and within sectors. Although a number of studies have calculated the shadow price of GHG emissions, these studies have employed country-level or industry-level data or a small sample of firm-level data in one country. This new data from a worldwide firm analysis of the shadow price of GHG emissions can play an important role in developing climate policy and promoting sustainable development.     

Reconciling Oil Palm Expansion and Climate Change Mitigation in Kalimantan,Indonesia

Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world’s most abundant vegetable oil and a commodity that has contributed significantly to Indonesia’s economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4–211.4 MtCO₂ yr^-1 under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55–60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia’s national emissions mitigation goal, while allowing oil palm area to double.     

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

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

Livestock greenhouse gas emissions and mitigation potential in Europe

The livestock sector contributes considerably to global greenhouse gas emissions (GHG). Here, for the year 2007 we examined GHG emissions in the EU27 livestock sector and estimated GHG emissions from production and consumption of livestock products; including imports, exports and wastage. We also reviewed available mitigation options and estimated their potential. The focus of this review is on the beef and dairy sector since these contribute 60% of all livestock production emissions. Particular attention is paid to the role of land use and land use change (LULUC) and carbon sequestration in grasslands. GHG emissions of all livestock products amount to between 630 and 863 Mt CO₂e, or 12–17% of total EU27 GHG emissions in 2007. The highest emissions aside from production, originate from LULUC, followed by emissions from wasted food. The total GHG mitigation potential from the livestock sector in Europe is between 101 and 377 Mt CO₂e equivalent to between 12 and 61% of total EU27 livestock sector emissions in 2007. A reduction in food waste and consumption of livestock products linked with reduced production, are the most effective mitigation options, and if encouraged, would also deliver environmental and human health benefits. Production of beef and dairy on grassland, as opposed to intensive grain fed production, can be associated with a reduction in GHG emissions depending on actual LULUC emissions. This could be promoted on rough grazing land where appropriate.     

Analyzing Economic and Environmental Performance of Switchgrass Biofuel Supply Chains

This study optimized the net present value (NPV) of profit of various switchgrass-based ethanol supply chains and estimated associated greenhouse gas (GHG) emissions in west Tennessee. Three configurations of feedstock harvesting and storage, including a large round baler system, a large square baler system, and a chopping/densification system, were evaluated. A mixed-integer mathematical programming model incorporating high-resolution spatial data was used to determine the optimal locations and capacities of cellulosic ethanol plants and feedstock preprocessing facilities, and associated feedstock-draw areas by maximizing the NPV of profit over 20 years. The optimized outputs were then used to estimate the GHG emissions produced in the biofuel supply chain (BSC) per year. The study shows that BSC configurations have important implications for the economic and environmental performance of the system. The harvest and storage configurations affect the locations of conversion and preprocessing facilities, and associated feedstock-draw areas, hence impacting the cost and emissions of both feedstock and biofuels transportation. The findings suggest the BSC system that harvests feedstock with forage choppers and utilizes stretch-wrap balers to increase feedstock density has the highest NPV of profit. The BSC system that uses large square balers for harvest and storage emits the lowest amount of GHGs per year. In addition, the sensitivity analysis suggests that biofuel price and scaling factor of facility capital was influential to the economics of BSC systems. The breakeven price of biofuel for the three BSCs was around $0.97 L^?1.     

Ecosystem model parameterization and adaptation for sustainable cellulosic biofuel landscape design

Renewable fuel standards in the US and elsewhere mandate the production of large quantities of cellulosic biofuels with low greenhouse gas (GHG) footprints, a requirement which will likely entail extensive cultivation of dedicated bioenergy feedstock crops on marginal agricultural lands. Performance data for such systems is sparse, and non‐linear interactions between the feedstock species, agronomic management intensity, and underlying soil and land characteristics complicate the development of sustainable landscape design strategies for low‐impact commercial‐scale feedstock production. Process‐based ecosystem models are valuable for extrapolating field trial results and making predictions of productivity and associated environmental impacts that integrate the effects of spatially variable environmental factors across diverse production landscapes. However, there are few examples of ecosystem model parameterization against field trials on both prime and marginal lands or of conducting landscape‐scale analyses at sufficient resolution to capture interactions between soil type, land use, and management intensity. In this work we used a data‐diverse, multi‐criteria approach to parameterize and validate the DayCent biogeochemistry model for upland and lowland switchgrass using data on yields, soil carbon changes, and soil nitrous oxide emissions from US field trials spanning a range of climates, soil types, and management conditions. We then conducted a high‐resolution case study analysis of a real‐world cellulosic biofuel landscape in Kansas in order to estimate feedstock production potential and associated direct biogenic GHG emissions footprint. Our results suggest that switchgrass yields and emissions balance can vary greatly across a landscape large enough to supply a biorefinery in response to variations in soil type and land‐use history, but that within a given land base both of these performance factors can be widely modulated by changing management intensity. This in turn implies a large sustainable cellulosic biofuel landscape design space within which a system can be optimized to meet economic or environmental objectives.     

Uncertainty Analysis in Biofuel Systems

This article evaluates the implications of uncertainty in the life cycle (LC) energy efficiency and greenhouse gas (GHG) emissions of rapeseed oil (RO) as an energy carrier displacing fossil diesel (FD). Uncertainties addressed include parameter uncertainty as well as scenario uncertainty concerning how RO coproduct credits are accounted for (uncertainty due to modeling choices). We have carried out an extensive data collection to build an LC inventory accounting for parameter uncertainty. Different approaches for carbon stock changes associated with converting set‐aside land to rapeseed cultivation have been considered, which result in different values: from ?0.25 t C/ha.yr (carbon uptake by the soil in tonnes per hectare year) to 0.60 t C/ha.yr (carbon emission). Energy renewability efficiency and GHG emissions of RO are presented, which show the influence of parameter versus scenario uncertainty. Primary energy savings and avoided GHG emissions when RO displaces FD have also been calculated: Avoided GHG emissions show considerably higher uncertainty than energy savings, mainly due to land use (nitrous oxide emissions from soil) and land use conversion (carbon stock changes). Results demonstrate the relevance of applying uncertainty approaches; emphasize the need to reduce uncertainty in the environmental life cycle modeling, particularly GHG emissions calculation; and show the importance of integrating uncertainty into the interpretation of results.     

Sensitivity of the carbon footprint of New Zealand milk to greenhouse gas metrics

Milk production is responsible for emitting a range of greenhouse gases (GHGs), mainly carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄). In Life Cycle Assessments (LCA), the Global Warming Potential with a time horizon of 100 years (GWP100) is used almost universally to aggregate emissions of individual gases into so-called CO₂-equivalent emissions that are used to calculate the overall carbon footprint of milk production. However, there is growing awareness that, depending on the purpose of the LCA, metrics other than GWP100 could be justified and some would give a very different weighting for the short-lived gas CH₄ relative to the long-lived gases CO₂ and N₂O when calculating the carbon footprint. Pastoral dairy production systems at different levels of intensification differ in the balance of short- and long-lived GHGs associated with on- and off-farm emissions. Differences in the carbon footprint of different production systems could therefore be highly sensitive to the choice of GHG metric. Here we explore the extent to which alternative GHG metric choices would alter the carbon footprint of New Zealand milk production at different levels of intensification at national, regional and individual farm scales and compared to the carbon footprint of milk of selected European countries. We find that the ranking of different production systems and individual farms in terms of their carbon footprint is relatively robust against the choice of GHG metric, despite significant differences in their utilisation of pastures versus supplementary off-farm feed, fertiliser use and energy consumption at various stages of farm operations. However, there are instances where alternative GHG metric choices would fundamentally change the conclusions of LCA of different production systems, including whether a move towards higher or lower input systems would increase or decrease the average carbon footprint of milk production in New Zealand. Greater transparency about the implications of alternative GHG metrics for LCA, and the often inadvertent and implicit value judgements embedded in these metrics, would help ensure that policy decisions and consumer choices based on LCA indeed deliver the climate outcomes intended by end-users.     

Land use of drained peatlands: Greenhouse gas fluxes,plant production,and economics

Drained peatlands are hotspots for greenhouse gas (GHG) emissions, which could be mitigated by rewetting and land use change. We performed an ecological/economic analysis of rewetting drained fertile peatlands in a hemiboreal climate using different land use strategies over 80 years. Vegetation, soil processes, and total GHG emissions were modeled using the CoupModel for four scenarios: (1) business as usual—Norway spruce with average soil water table of ?40 cm; (2) willow with groundwater at ?20 cm; (3) reed canary grass with groundwater at ?10 cm; and (4) a fully rewetted peatland. The predictions were based on previous model calibrations with several high‐resolution datasets consisting of water, heat, carbon, and nitrogen cycling. Spruce growth was calibrated by tree‐ring data that extended the time period covered. The GHG balance of four scenarios, including vegetation and soil, were 4.7, 7.1, 9.1, and 6.2 Mg CO₂eq ha^?1 year^?1, respectively. The total soil emissions (including litter and peat respiration CO₂ + N₂O + CH₄) were 33.1, 19.3, 15.3, and 11.0 Mg CO₂eq ha^?1 year^?1, respectively, of which the peat loss contributed 35%, 24%, and 7% of the soil emissions for the three drained scenarios, respectively. No peat was lost for the wet peatland. It was also found that draining increases vegetation growth, but not as drastically as peat respiration does. The cost–benefit analysis (CBA) is sensitive to time frame, discount rate, and carbon price. Our results indicate that the net benefit was greater with a somewhat higher soil water table and when the peatland was vegetated with willow and reed canary grass (Scenarios 2 and 3). We conclude that saving peat and avoiding methane release using fairly wet conditions can significantly reduce GHG emissions, and that this strategy should be considered for land use planning and policy‐making.     

Reducing methane on-farm by feeding diets high in fat may not always reduce life cycle greenhouse gas emissions

Purpose

To consider whether feed supplements that reduce methane emissions from dairy cows result in a net reduction in greenhouse gas (GHG) intensity when productivity changes and emissions associated with extra manufacturing and management are included.

Methods

A life cycle assessment was undertaken using a model farm based on dairy farms in Victoria, Australia. The system boundary included the creation of farm inputs and on-farm activities up to the farm gate where the functional unit was 1 L of fat and protein corrected milk (FPCM). Electricity and diesel (scaled per cow), and fertiliser inputs (scaled on farm size) to the model farm were based on average data from a survey of farms. Fertiliser applied to crops was calculated per area of crop. Animal characteristics were based on available data from farms and literature. Three methane-reducing diets (containing brewers grain, hominy or whole cotton seed) and a control diet (cereal grain) were modelled as being fed during summer, with the control diet being fed for the remainder of the year in all cases.

Results and discussion

Greenhouse gas intensity (kg CO₂-eq/L FPCM) was lower than the control diet when the hominy (97 % compared with control) and brewers grain (98 %) diets were used but increased when the whole cottonseed diet was used (104 %). On-farm GHG emissions (kg CO₂-eq) were lower than the control diet when any of the methane-reducing diets were used (98 to 99.5 % of emissions when control diet fed). Diesel use in production and transport of feed supplements accounted for a large portion (63 to 93 %) of their GHG intensity (kg CO₂-eq/t dry matter). Adjusting fertiliser application, changing transport method, changing transport fuel, and using nitrification inhibitors all had little effect on GHG emissions or GHG intensity.

Conclusions

Although feeding strategies that reduce methane emissions from dairy cows can lower the GHG emissions up to the farm gate, they may not result in lower GHG intensities (g CO₂-eq/L FPCM) when pre-farm emissions are included. Both transport distance and the effect of the feed on milk production have important impacts on the outcomes.