Variability Of Greenhouse Gas Emissions Research Articles

Characterisation and variability of greenhouse gas emissions from biomethane production via anaerobic digestion of maize

Biomethane is a renewable gas that can be used in existing infrastructure to reduce dependency on natural gas and lower greenhouse gas (GHG) emissions. Policy incentives have promoted a rapid implementation of biomethane production facilities using anaerobic digestion (AD). A range of feedstocks are used in AD including crops which have a higher GHG burden than most wastes and residues. The purpose of this research is to characterise and assess GHG emissions from typical operational biomethane facilities. It is imperative that GHG savings are obtained therefore quantifying emissions using a robust methodology is paramount. This study uses maize as a case study utilising data from several farms and AD facilities. Results show that calculated emissions for biomethane production from maize are 33.8 gCO2e/MJ of biomethane using the Renewable Energy Directive (RED) methodology. Key emission sources include N-fertiliser production, soil N2O emissions, imported electricity use, and fugitive methane. Sensitivity analysis performed assessed key data inputs and demonstrates how input inventory parameters affect the GHG balance and highlights variability in results. For the desired GHG savings to be achieved it is important that operators minimise fertiliser use, use nitrogen inhibitors, minimise imported electricity, and undertake close management of methane loss. This paper shows that although biomethane is considered a renewable, low carbon fuel, the inputs need to be carefully managed in order to achieve this.

Are secondary forests second-rate? Comparing peatland greenhouse gas emissions, chemical and microbial community properties between primary and secondary forests in Peninsular Malaysia

Tropical peatlands are globally important ecosystems with high C storage and are endangered by anthropogenic disturbances. Microbes in peatlands play an important role in sustaining the functions of peatlands as a C sink, yet their characteristics in these habitats are poorly understood. This research aimed to elucidate the responses of these complex ecosystems to disturbance by exploring greenhouse gas (GHG) emissions, nutrient contents, soil microbial communities and the functional interactions between these components in a primary and secondary peat swamp forest in Peninsular Malaysia. GHG measurements using closed chambers, and peat sampling were carried out in both wet and dry seasons. Microbial community phenotypes and nutrient content were determined using phospholipid fatty acid (PLFA) and inductively-coupled plasma mass spectrometry (ICP-MS) analyses respectively. CO2 emissions in the secondary peat swamp forest were > 50% higher than in the primary forest. CH4 emission rates were ca. 2 mg m−2 h−1 in the primary forest but the secondary forest was a CH4 sink, showing no seasonal variations in GHG emissions. Almost all the nutrient concentrations were significantly lower in the secondary forest, postulated to be due to nutrient leaching via drainage and higher rates of decomposition. Cu and Mo concentrations were negatively correlated with CO2 and CH4 emissions respectively. Microbial community structure was overwhelmingly dominated by bacteria in both forest types, however it was highly sensitive to land-use change and season. Gram-positive and Gram-negative relative abundance were positively correlated with CO2 and CH4 emissions respectively. Drainage related disturbances increased CO2 emissions, by reducing the nutrient content including some with known antimicrobial properties (Cu & Na) and by favouring Gram-positive bacteria over Gram-negative bacteria. These results suggest that the biogeochemistry of secondary peat swamp forest is fundamentally different from that of primary peat swamp forest, and these differences have significant functional impacts on their respective environments.

Extreme drought boosts CO2 and CH4 emissions from reservoir drawdown areas

ABSTRACTAlthough previous studies suggest that greenhouse gas (GHG) emissions from reservoir sediment exposed to the atmosphere during drought may be substantial, this process has not been rigorously quantified. Here we determined carbon dioxide (CO2) and methane (CH4) emissions from sediment cores exposed to a drying and rewetting cycle. We found a strong temporal variation in GHG emissions with peaks when the sediment was drained (C emissions from permanently wet sediment and drained sediments were, respectively, 251 and 1646 mg m−2 d−1 for CO2 and 0.8 and 547.4 mg m−2 d−1 for CH4) and then again during rewetting (C emissions from permanently wet sediment and rewetted sediments were, respectively, 456 and 1725mg m−2 d−1 for CO2 and 1.3 and 3.1 mg m−2 d−1 for CH4). To gain insight into the importance of these emissions at a regional scale, we used Landsat satellite imagery to upscale our results to all Brazilian reservoirs. We found that during the extreme drought of 2014–2015, an additional 1299 km2 of sediment was exposed, resulting in an estimated emission of 8.5 × 1011 g of CO2-eq during the first 15 d after the overlying water disappeared and in the first 33 d after rewetting, the same order of magnitude as the year-round GHG emissions of large (∼mean surface water area 454 km2) Brazilian reservoirs, excluding the emissions from the draw-down zone. Our estimate, however, has high uncertainty, with actual emissions likely higher. We therefore argue that the effects of drought on reservoir GHG emissions merits further study, especially because climate models indicate an increase in the frequency of severe droughts in the future. We recommend incorporation of emissions during drying and rewetting into GHG budgets of reservoirs to improve regional GHG emission estimates and to enable comparison between GHG emissions from hydroelectric and other electricity sources. We also emphasize that peak emissions at the onset of drought and the later rewetting should be quantified to obtain reliable emission estimates.

A review of life cycle greenhouse gas (GHG) emissions of commonly used ex-situ soil treatment technologies

Abstract GHG emissions are important footprints because of increasing concern over climate change. Remediation methods produces GHGs in varying quantities based on which activities are involved through its entire life cycle and which contaminants are present, often because some contaminants are more difficult to remove from soil than others. Accounting for emissions from all phases of the project requires a life cycle assessment (LCA) approach. LCA can help in choosing the best available technology to reduce the environmental burden of the remediation technology or to improve the sustainability of the technology by implementing systematic approaches to ensure that future developments are optimized for environmental performance throughout the life cycle. The primary objective of this paper is to review existing LCA studies that report GHG emissions (CO2-eq) or Global warming potential (GWP) from six ex-situ soil remediation technologies (ESRTs), including excavation and disposal, ex-situ thermal desorption, ex-situ soil vapor extraction, ex-situ bioremediation, excavation and incineration, and soil washing, and present the variability in GHG/GWP results and how this data can help in selecting an ex-situ soil remediation technology with a lower global warming potential. A second objective of this study is to compare the GWP levels of ex-situ remediation to the GWP levels of typical in situ remediation methods. Our results showed a large variation in GHG emissions of treated soil from six ESRTs varying from 3.1 × 10−7 t to 8.2 t CO2-eq/m3. Incineration had the highest mean GHG emissions (0.7 t CO2-eq/m3) and thermal desorption the lowest (0.07 t CO2-eq/m3). It was also found that there was a large variation range of GHG emissions from the ex-situ excavation and disposal method soil treatment technologies, varying from 3.1 × 10−7 t to 8.2 t CO2-eq/m3 of treated soil. This knowledge provides opportunities to increase sustainability of soil remediation throughout the investigation, design, construction, operation, and monitoring phases of site remediation regardless of the selected cleanup remedy. This shows data on LCA GHGs are useful to assess the impact of different scenarios and management practices on ESRTs.

Statistically Enhanced Model of In Situ Oil Sands Extraction Operations: An Evaluation of Variability in Greenhouse Gas Emissions.

Greenhouse gas (GHG) emissions associated with extraction of bitumen from oil sands can vary from project to project and over time. However, the nature and magnitude of this variability have yet to be incorporated into life cycle studies. We present a statistically enhanced life cycle based model (GHOST-SE) for assessing variability of GHG emissions associated with the extraction of bitumen using in situ techniques in Alberta, Canada. It employs publicly available, company-reported operating data, facilitating assessment of inter- and intraproject variability as well as the time evolution of GHG emissions from commercial in situ oil sands projects. We estimate the median GHG emissions associated with bitumen production via cyclic steam stimulation (CSS) to be 77 kg CO2eq/bbl bitumen (80% CI: 61-109 kg CO2eq/bbl), and via steam assisted gravity drainage (SAGD) to be 68 kg CO2eq/bbl bitumen (80% CI: 49-102 kg CO2eq/bbl). We also show that the median emissions intensity of Alberta's CSS and SAGD projects have been relatively stable from 2000 to 2013, despite greater than 6-fold growth in production. Variability between projects is the single largest source of variability (driven in part by reservoir characteristics) but intraproject variability (e.g., startups, interruptions), is also important and must be considered in order to inform research or policy priorities.

An Environmental Tax Towards More Sustainable Food: Empirical Evidence of the Consumption of Animal Products in France

Agricultural production is among the industries with the highest impact on the environment in terms of greenhouse gas (GHG) emissions, especially in the production of ruminant meats. Households can change their food consumption habits so as to consume less polluting products such as white meat or vegetable-based food. We analyze whether or not a CO2 equivalent (CO2-eq) tax policy in France can change household habits with respect to animal product purchases, and their environmental impact. Using two levels of a CO2-eq tax (€56 and €200 per tonne of CO2-eq) applied to the consumption of all animal products, only ruminant meats or only beef, we show that a high level of tax does not allow meeting the 20% objective threshold of GHG emissions reduction for 2020 since it would lead to a 6% decrease in GHG emissions only. Despite the weak effect of such a tax, the most efficient scenario would be to tax the consumption of beef only at a high level. Indeed, this tax policy would allow reaching a 3.2% decrease in GHG emissions, that represents 53% of the variation in GHG emissions when all products are taxed whereas it would only generate 12% of the household welfare damages.

Quantifying drivers of variability in life cycle greenhouse gas emissions of consumer products\u2014a case study on laundry washing in Europe

PurposeVariability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.MethodsData from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.Results and discussionBoth inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5 × 102 g CO2−eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.ConclusionsThe combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

Diurnal and seasonal variations of greenhouse gas emissions from a naturally ventilated dairy barn in a cold region

Carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions were quantified for a naturally ventilated free-stall dairy barn in the Canadian Prairies climate through continuous measurements for a year from February 2015 to January 2016, with ventilation rate estimated by a CO2 mass balance method. The results were categorized into seasonal emission profiles with monthly data measured on a typical day, and diurnal profiles in cold (January), warm (July), and mild seasons (October) of all three gases. Seasonal CO2, CH4, and N2O concentrations greatly fluctuated within ranges of 593–2433 ppm, 15–152 ppm, and 0.32–0.40 ppm, respectively, with obviously higher concentrations in the cold season. Emission factors of the three gases were summarized: seasonal N2O emission varied between 0.5 and 10 μg s−1 AU−1 with lower emission in the cold season, while seasonal CO2 and CH4 emissions were within narrow ranges of 112–119 mg s−1 AU−1 and 2.5–3.5 mg s−1 AU−1. The result suggested a lower enteric CH4 emission for dairy cows than that estimated by Environment Canada (2014). Significant diurnal effects (P < 0.05) were observed for CH4 emissions in all seasons with higher emissions in the afternoons and evenings. The total greenhouse gas (GHG) emission, which was calculated by summing the three GHG in CO2 equivalent, was mainly contributed by CO2 and CH4 emissions and showed no significant seasonal variations (P > 0.05), but obvious diurnal variations in all seasons. In comparison with previous studies, it was found that the dairy barn in a cold region climate with smaller vent openings had relatively higher indoor CO2 and CH4 concentrations, but comparable CO2 and CH4 emissions to most previous studies. Besides, ventilation rate, temperature, and relative humidity all significantly affected the three gas concentrations with the outdoor temperature being the most relevant factor (P < 0.01); however, they showed less or no statistical relations to emissions.

Short-term dynamics of greenhouse gas emissions and cultivable bacterial populations in response to induced and natural disturbances in organically and conventionally managed soils

Organically managed (ORG) soil is often considered healthier than conventionally managed (CONV) soil, with greater resistance and resilience to disturbances, as evidenced by reduced oscillations in bacterial populations and activities. Greenhouse gas (GHG) fluxes are mediated by bacterial processes, but variations in GHG emissions have not been related to bacterial oscillations in soil. Two environmentally controlled and two field experiments were set up to compare oscillations in bacterial colony-forming-units (CFUs) and GHG (nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4)) fluxes after disturbances in ORG and CONV soils. Soil amendment with grass-clover (GC) or cattle manure (CM) resulted in peaks in N2O and CO2 emission, followed by CFUs. CH4 temporarily increased in GC- but decreased in CM-amended soil. Ratios of CFUs and GHGs in amended over nonamended soils oscillated during three weeks, mostly with lower frequencies and amplitudes in ORG soils. Fluctuations were more irregular in field soils, but significant oscillations were detected after irrigation or intensive rain in summer. Cross correlations between variables showed several significant sequences of microbial processes under controlled conditions but not in the field. Average GHG emissions were higher from ORG soil than CONV soil under these conditions, indicating that these have to be taken into consideration when estimating soil health.

Effects of optimized N fertilization on greenhouse gas emission and crop production in the North China Plain

Improving nitrogen (N) efficiency and reducing greenhouse gas (GHG) emissions are dual challenges of the agricultural sector in the North China Plain (NCP). Most relevant studies conducted in the NCP lasted only 1–2 years without sufficiently addressing the temporal variations of weather conditions and farming practices over different seasons. Thus, a 4-year (2008–2012) field experiment was conducted for a wheat–maize cropping system in a typical intensive agricultural region of the NCP. The three N application rates were (a) control without N application (CK); (b) farmers’ conventional N fertilization (CON), i.e., 600kgNha−1yr−1; and (c) optimized N fertilization (OPT), i.e., 420kgNha−1yr−1. Emissions of nitrous oxide (N2O) and methane (CH4), N uptake and crop production were measured. Compared with CON, the annual cumulative N2O emissions from OPT decreased by 40.9%, 7.2%, and 22.3% during the 2008–2009, 2009–2010 and 2011–2012 rotation years, respectively. Basal N fertilization in the wheat season was the critical period for N2O mitigation, although the maize season contributed 51%–89% of the annual N2O emission. CH4 uptake (CO2-equivalent) via soil accounted for 60%–96% of N2O in CK treatment and 4%–48% in fertilization treatments, indicating that CH4 should be considered in the overall GHG emissions from crop production. Compared with CON, OPT significantly improved N efficiency by 46%–52% for wheat and maize and maintained a similar or higher crop yield. Improvements in N efficiency should focus on the maize season. Water saving practices exhibited high potential to reduce indirect GHG emissions for the entire life cycle of crop production. Compared with CON, OPT significantly reduced the GHG intensity, particularly in the wheat season. Future long-term field experiments are required to account for considerable variations in GHG emissions and crop production under field conditions in the NCP.

Greenhouse Gas Emissions from Stored Dairy Slurry from Multiple Farms.

A significant need exists to improve our understanding of the extent of greenhouse gas emissions from the storage of livestock manure to both improve the reliability of inventory assessments and the impact of beneficial management practice adoption. Factors affecting the extent and variability of greenhouse gas emissions from stored dairy manure were investigated. Emissions from six slurries stored in clean concrete tanks under identical "warm-season" conditions were monitored consecutively over 173 d (18°C average air temperature). Methane (CH) emissions varied considerably among the manures from 6.3 to 25.9 g m d and accounted for ∼96% of the total CO equivalent greenhouse gas emissions. The duration of the lag period, when methane emissions were near baseline levels, varied from 30 to 90 d from the beginning of storage. As a result, CH emissions were poorly correlated with air temperature prior to the time of peak emissions (i.e., the initial 48 to 108 d of storage) but improved afterward. The air temperature following the time of the peak CH flux and the length of the active methanogenesis period (i.e., when the daily CH emissions ≥ 7.6 g m d) were highly correlated with CH emissions ( = 0.98, < 0.01). Methane conversion factors (MCFs) ranged from 0.08 to 0.52 for the different manures. The MCFs generated from existing CH emission models were correlated ( = 0.68, = 0.02) to MCFs calculated for the active methanogenesis period for manure containing wood bedding. A temperature component was added that improved the accuracy ( = 0.82, < 0.01). This demonstrated that an improved understanding of lag period dynamics will enhance stored dairy manure greenhouse gas emission inventory calculations.

STOCHASTIC CARBON EMISSION ESTIMATION METHOD FOR CONSTRUCTION OPERATION

Low carbon construction is an important operation management goal because greenhouse gas (GHG) reduc­tion has become a global concern. Major construction resources that contribute GHG, such as equipment and labour, are being targeted to achieve this goal. The GHG emissions produced by the resources vary with their operating conditions. It is commendable to provide a statistical GHG emission estimation method that models the transitory nature of resource states at micro-scale of construction operations. This paper proposes a computational method called Stochastic Carbon Emission Estimation (SCE2) that measures the variability of GHG emissions. It creates construction operation models consisting of atomic work tasks, utilizes hourly equipment fuel consumption and hourly labourer respiratory rates that change according to their operating conditions classified into five categories, and identifies an optimal resource combi­nation by trading off eco-economic performance metrics such as the amount of GHG emissions, operation completion time, operation completion cost, and productivity. The study is of value to researchers because SCE2 fill in a gap to eco-economic operation modelling and analysis tool which considers operating conditions at micro-scale of construction operation having many stochastic work tasks. This study is also relevance to practitioners because it allows project man­agers to achieve eco-economic goals while honouring predefined constraints associated with time and cost.

Influence of climate variability and stocking strategies on greenhouse gas emissions (GHGE), production and profit of a northern Queensland beef cattle herd

Previous studies of greenhouse gas emissions (GHGE) from beef production systems in northern Australia have been based on models of ‘steady-state’ herd structures that do not take into account the considerable inter-annual variation in liveweight gain, reproduction and mortality rates that occurs due to seasonal conditions. Nor do they consider the implications of flexible stocking strategies designed to adapt these production systems to the highly variable climate. The aim of the present study was to quantify the variation in total GHGE (t CO2e) and GHGE intensity (t CO2e/t liveweight sold) for the beef industry in northern Australia when variability in these factors was considered. A combined GRASP–Enterprise modelling platform was used to simulate a breeding–finishing beef cattle property in the Burdekin River region of northern Queensland, using historical climate data from 1982–2011. GHGE was calculated using the method of Australian National Greenhouse Gas Inventory. Five different stocking-rate strategies were simulated with fixed stocking strategies at moderate and high rates, and three flexible stocking strategies where the stocking rate was adjusted annually by up to 5%, 10% or 20%, according to pasture available at the end of the growing season. Variation in total annual GHGE was lowest in the ‘fixed moderate’ (~9.5 ha/adult equivalent (AE)) stocking strategy, ranging from 3799 to 4471 t CO2e, and highest in the ‘fixed high’ strategy (~5.9 ha/AE), which ranged from 3771 to 7636 t CO2e. The ‘fixed moderate’ strategy had the least variation in GHGE intensity (15.7–19.4 t CO2e/t liveweight sold), while the ‘flexible 20’ strategy (up to 20% annual change in AE) had the largest range (10.5–40.8 t CO2e/t liveweight sold). Across the five stocking strategies, the ‘fixed moderate’ stocking-rate strategy had the highest simulated perennial grass percentage and pasture growth, highest average rate of liveweight gain (121 kg/steer), highest average branding percentage (74%) and lowest average breeding-cow mortality rate (3.9%), resulting in the lowest average GHGE intensity (16.9 t CO2e/t liveweight sold). The ‘fixed high’ stocking rate strategy (~5.9 ha/AE) performed the poorest in each of these measures, while the three flexible stocking strategies were intermediate. The ‘fixed moderate’ stocking strategy also yielded the highest average gross margin per AE carried and per hectare. These results highlight the importance of considering the influence of climate variability on stocking-rate management strategies and herd performance when estimating GHGE. The results also support a body of previous work that has recommended the adoption of moderate stocking strategies to enhance the profitability and ecological stability of beef production systems in northern Australia.

Greenhouse gas emission from direct seeded paddy fields under different soil water potentials in Eastern India

In the anticipated water scarcity and global warming scenario; it is imperative to identify suitable irrigation scheduling strategy in paddy fields for increasing water productivity and mitigating greenhouse gas (GHG) emissions. We conducted a two year (dry season of 2014 and 2015) field experiment for irrigation scheduling based on tensiometric measurement of soil water potential (SWP) in order to quantify temporal and seasonal variations in GHGs emissions and their trade off relationship at five levels of SWPs viz. SWP 1 (−20kPa), SWP 2 (−30kPa), SWP 3 (−40kPa), SWP 4 (−50kPa) and SWP 5 (−60kPa), in addition to the traditional practice of growing flooded rice (CF). Fluxes of methane (CH4) and nitrous oxide (N2O) during the growing period were measured using manual closed chamber-gas chromatograph and the carbon dioxide (CO2) flux was measured using an infrared CO2 analyzer. A significant decrease in seasonal cumulative CH4 emission (30–60.2%) was recorded at different SWPs as compared to CF. In contrast, emission of CO2 and N2O increased by 12.9–26.6% and 16.3–22.1% respectively at SWPs 1 and 2; conversely, a significant decrease in emissions of these gases were observed at higher SWPs (SWPs 3–5). Among different SWP treatments, irrigation scheduling at SWP 2 maintained yield at par with CF with water saving of 32.9–41.1% and reduced CH4 emission (43–44.1%). However, due to increase in CO2 and N2O emission at SWP 2, there was no significant reduction in global warming potential (GWP) as compared with CF. Among different rice growth stages GHGs emission were predominant during vegetative growth stage. Regression relationship of GHGs emission with key soil parameters was employed to predict seasonal emissions of GHGs from paddy field. The results of this study suggest that scheduling irrigation at SWP 2 can be an effective strategy in order to save water, maintain rice yield and mitigate CH4 emission from direct seeded paddy fields in eastern India, however further research is needed to identify suitable management strategy for reducing CO2 and N2O emissions at SWP 2 in order to reduce the GWP.

Multiyear greenhouse gas balances at a rewetted temperate peatland.

Drained peat soils are a significant source of greenhouse gas (GHG) emissions to the atmosphere. Rewetting these soils is considered an important climate change mitigation tool to reduce emissions and create suitable conditions for carbon sequestration. Long-term monitoring is essential to capture interannual variations in GHG emissions and associated environmental variables and to reduce the uncertainty linked with GHG emission factor calculations. In this study, we present GHG balances: carbon dioxide (CO2 ), methane (CH4 ) and nitrous oxide (N2 O) calculated for a 5-year period at a rewetted industrial cutaway peatland in Ireland (rewetted 7years prior to the start of the study); and compare the results with an adjacent drained area (2-year data set), and with ten long-term data sets from intact (i.e. undrained) peatlands in temperate and boreal regions. In the rewetted site, CO2 exchange (or net ecosystem exchange (NEE)) was strongly influenced by ecosystem respiration (Reco ) rather than gross primary production (GPP). CH4 emissions were related to soil temperature and either water table level or plant biomass. N2 O emissions were not detected in either drained or rewetted sites. Rewetting reduced CO2 emissions in unvegetated areas by approximately 50%. When upscaled to the ecosystem level, the emission factors (calculated as 5-year mean of annual balances) for the rewetted site were (±SD) -104±80g CO2 -C m-2 yr-1 (i.e. CO2 sink) and 9±2g CH4 -C m-2 yr-1 (i.e. CH4 source). Nearly a decade after rewetting, the GHG balance (100-year global warming potential) had reduced noticeably (i.e. less warming) in comparison with the drained site but was still higher than comparative intact sites. Our results indicate that rewetted sites may be more sensitive to interannual changes in weather conditions than their more resilient intact counterparts and may switch from an annual CO2 sink to a source if triggered by slightly drier conditions.

Variation of greenhouse gas emissions and identification of their drivers during the fattening of Belgian Blue White bulls based on a LCA approach

Greenhouse gas emission intensity (GHGI; kilograms carbon dioxide equivalents/kilograms liveweight gain) have to be reduced so as to limit the impact of human activities on global warming while furnishing food to human. In this respect, performances of 654 Belgian Blue double-muscled bulls (BBdm) during their fattening phase were recorded. On this basis, their greenhouse gas emissions were modelled to estimate variation in GHGI and investigate mitigation options at that level. The relevance of theses option is discussed, taking into account the whole life and production system scales. Large variations (mean (s.d.)) were observed (from 7.2 (0.4) to 10.0 (0.7) kg carbon dioxide equivalents/kg liveweight gain) for, respectively, the 1st- and 4th-quantile groups defined for GHGI. Early culling, low liveweight and age at start of the fattening phase of the bulls would lead to a reduction of GHGI. Nevertheless, more than 32% of the variation remained unexplained. However, decision leading to reduction of GHG intensity at this stage of the life may be compensated in the early stage of BBdm. Attention is drawn on the necessity to encompass the whole life of BBdm for investigating mitigation options and on the sensitivity of the results on models and methodological choices.

Spatial and temporal variability of greenhouse gas emissions from rural development land use operations

Climate change objectives of mitigation and adaptation are being mainstreamed into many policies and strategies around the world. In Europe, this has included the Rural Development Programme, which aims to tackle multiple social, economic and environmental objectives in rural areas, and the integration of climate change objectives adds another strand of complexity to the decision making process. When formulating policies determining the likely effectiveness of any particular measure can be challenging, especially with respect to the spatial and temporal variability of greenhouse gas emissions. This is a challenge faced by all countries and regions around the world. This study uses Europe as an example to explore this issue. It highlights the variability in emissions from land use operations that may be encountered under different conditions and time horizons and considers this in the context of policy formulation. The Optimal Strategies for Climate change Action in Rural Areas software has been adapted to derive net greenhouse gas emissions for rural development operations for all regions in Europe. Operations have been classified into five categories based on their benefit/burden over different time horizons. The analysis shows that it is important to understand the time period over which benefits or burdens are realised and determine how this fits with policy instruments, such as land management agreements and the permanency of actions. It also shows that in some regions an operation can have benefits, but in other regions it has burdens; thus, location can be critical. Finally, in the context of developing operations to meet multiple social, economic and environmental objectives, it is important to acknowledge that seeking options that only reduce emissions may not always be practical or possible. In some instances, we may have to accept an increase in emissions in order to meet other objectives. It is important that we evaluate the net greenhouse gas emissions of all operations, not just those aimed at climate change mitigation. We can then select those with the least burden in the process of developing optimal solutions to meet multiple objectives.

Dynamic fleet-based life-cycle greenhouse gas assessment of the introduction of electric vehicles in the Portuguese light-duty fleet

Reducing greenhouse gas (GHG) emissions from the transportation sector is the goal of several current policies and battery electric vehicles (BEVs) are seen as one option to achieve this goal. However, the introduction of BEVs in the fleet is gradual and their benefits will depend on how they compare with increasingly more energy-efficient internal combustion engine vehicles (ICEVs). The aim of this article is to assess whether displacing ICEVs by BEVs in the Portuguese light-duty fleet is environmentally beneficial (focusing on GHG emissions), taking into account the dynamic behavior of the fleet. A dynamic fleet-based life-cycle assessment (LCA) of the Portuguese light-duty fleet was performed, addressing life-cycle (LC) GHG emissions through 2030 across different scenarios. A model was developed, integrating: (i) a vehicle stock sub-model of the Portuguese light-duty fleet; and (ii) dynamic LC sub-models of three vehicle technologies (gasoline ICEV, diesel ICEV and BEV). Two metrics were analyzed: (i) Total fleet LC GHG emissions (in Mton CO2 eq); and (ii) Fleet LC GHG emissions per kilometer (in g CO2 eq/km). A sensitivity analysis was performed to assess the influence of different parameters in the results and ranking of scenarios. The model baseline projected a reduction of 30–39 % in the 2010–2030 fleet LC GHG emissions depending on the BEV fleet penetration rate and ICEV fuel consumption improvements. However, for BEV introduction in the fleet to be beneficial compared to an increasingly more efficient ICEV fleet, a high BEV market share and electricity emission factor similar or lower to the current mix (485 g CO2 eq/kWh) need to be realized; these conclusions hold for the different conditions analyzed. Results were also sensitive to parameters that affect the fleet composition, such as those that change the vehicle stock, the scrappage rate, and the activity level of the fleet (11–19 % variation in GHG emissions in 2030), which are seldom assessed in the LCA of vehicles. The influence of these parameters also varies over time, becoming more important as time passes. These effects can only be captured by assessing Total fleet GHG emissions over time as opposed to the GHG emissions per kilometer metric. These results emphasize the importance of taking into account the dynamic behavior of the fleet, technology improvements over time, and changes in vehicle operation and background processes during the vehicle service life when assessing the potential benefits of displacing ICEVs by BEVs.

Greenhouse gas emission and storage in a small shallow lake

Small lakes are likely to show considerable temporal variability in greenhouse gas emissions given their transient stratification and short residence time. To determine the extent that CO2 and CH4 emission and storage depends on surface meteorology, we studied a shallow lake during 2 years with contrasting rainfall and thermal stratification. Gas fluxes were estimated with wind-based and surface renewal models and compared to direct measurements obtained with floating chambers. The assessment of greenhouse gases storage revealed that the lake gained CO2 in association with rainfall in both the rainier (2011) and drier summer (2012). In 2011, stratification was less extensive and disrupted frequently. The lake was a source of CO2 and CH4, and ebullition exceeded diffusive fluxes of CH4. In 2012, stratification was more persistent, the lake was a sink for CO2 during dry periods, CO2 and CH4 accumulated in the hypolimnion later in the summer when rainfall increased, diffusive fluxes of CH4 were similar to those in 2011 mid-summer and over four times higher during overturn. Ebullition was lower in the drier summer. Fluxes measured with chambers were closer to estimations from the surface renewal model and about two times values estimated with wind-based models.

Greenhouse gas emissions variation and corporate performance in international companies

The purpose of this study is to analyse the impact that variations in greenhouse gas emissions (2007-2008) had on corporate performance during three time periods. The empirical analysis was performed in two stages: 1) analysis of the data obtained through content analysis; 2) analysis of the factors that influence corporate performance using a dependency model - a multiple linear regression. The findings of this work can be considered of great interest on the international level because on the one hand they show a reduction in greenhouse gas emissions by firms pertaining to strategic sectors in this sense, and on the other a dependence model is established to test how the variation in emissions affects firm performance under the resource-based view theory. Furthermore, certain control variables are considered, such as capital intensity, public pressure, and firm growth rate, which until now have seldom been analysed in this context.