• Energy Research

Agriculture is the largest source of ammonia (NH3) emissions. As NH3 is an indirect greenhouse gas, NH3 measurements are crucial to improving greenhouse gas emission inventory estimates. Moreover, NH3 emissions have wider implications for environmental and human health. Only a few studies have measured NH3 emissions from pastures in the tropics and subtropics and none has compared emissions to inventory estimates. The objectives of this study were to (1) measure NH3 emissions from dairy pastures in tropical and subtropical regions; (2) calculate NH3 emissions factors (EF) for each campaign; and (3) compare measured EF with those based on the 2006 Intergovernmental Panel on Climate Change (IPCC) Tier 1, 2019 Refinement to the 2006 IPCC Tier 1, and the European Monitoring and Evaluation Programme/European Environmental Agency (EMPE/EEA) Tier 2 inventory estimates. Pasture NH3 emissions were measured on 3 dairy farms in Costa Rica. On each dairy, NH3 emissions were measured twice during the wet season and once during the dry season using a micrometeorological integrated horizontal-flux mass-balance method. Emissions were measured from excreta (dung and urine) deposited by grazing cattle and the subsequent application of organic (slurry) or synthetic fertilizer (ammonium nitrate or urea). Measured EF for all campaigns [from grazing cattle excreta and any subsequent slurry or fertilizer application; 4.9 ± 0.9% of applied nitrogen (mean ± SE)] were similar to those of the EMEP/EEA Tier 2 approach (6.1 ± 0.9%; mean ± SE) and 4 times lower than 2006 IPCC and 2019 Refinement to 2006 IPCC Tier 1 default estimates (17.7 ± 1.4 and 18.2 ± 0.9%, respectively; mean ± SE). Measured EF for excreta deposited on pasture and excreta both deposited on pasture and slurry application [3.9 ± 2.1 and 4.2 ± 2.1% (mean ± 95% CI), respectively] were 5 times lower than default EF assumed by 2006 IPCC and 2019 Refinement to 2006 IPCC methodology (both 20 and 21%, respectively), whereas EMEP/EAA estimates were similar [6.0 and 4.6 ± 0.3% (mean ± 95% CI), respectively]. This suggests an overestimation of EF from excreta deposited on pasture and slurry applications in tropical and subtropical regions by IPCC methodologies. Furthermore, rainfall, which is not included as a parameter in the current EMEP/EEA Tier 2 methodology, appeared to reduce NH3 emissions, suggesting that accounting for this in the inventory methodologies could improve inventory estimates.

This study compares dry matter losses and quality changes during the storage of SRC willow as chips and as rods. A wood chip stack consisting of approximately 74 tonnes of fresh biomass, or 31 tonnes dry matter (DM) was built after harvesting in the spring. Three weeks later, four smaller stacks of rods with an average weight of 0.8 tonnes, or 0.4 tonnes DM were built. During the course of the experiment temperature recorders placed in the stacks found that the wood chip pile reached 60 °C within 10 days of construction, but the piles of rods remained mostly at ambient temperatures. Dry matter losses were calculated by using pre-weighed independent samples within the stacks and by weighing the whole stack before and after storage. After 6 months the wood chip stack showed a DM loss of between 19.8 and 22.6%, and mean losses of 23.1% were measured from the 17 independent samples. In comparison, the rod stacks showed an average stack DM loss of between 0 and 9%, and between 1.4% and 10.6% loss from the independent samples. Analysis of the stored material suggests that storing willow in small piles of rods produces a higher quality fuel in terms of lower moisture and ash content; however, it has a higher fine content compared to storage in chip form. Therefore, according to the two storage methods tested here, there may be a compromise between maximising the net dry matter yield from SRC willow and the final fine content of the fuel.

This study examined the dry matter losses and the greenhouse gas (GHG) concentrations within two short rotation coppice (SRC) willow wood chip storage heaps. One heap was built on a grassland area (East Midlands) and the other (Rothamsted) on a concrete hard standing. A series of 1- and 3-m probes were embedded in the heaps in order to retrieve gas samples for analysis, and pre-weighed net bags were positioned in the core of the heap to detect dry matter losses. The bagged samples showed dry matter losses of 18 and 19 % in the East Midlands and Rothamsted heaps after 210 and 97 days storage, respectively. The Rothamsted heap showed a whole-heap dry matter loss of 21 %. During this time, the wood chips dried from 54 to 39 % moisture content in the East Midlands heap and 50 to 43 % at Rothamsted. The results from analysing the whole Rothamsted heap indicated an overall loss of 1.5 GJ per tonne stored, although measurements from bagged samples in the core suggested that the chips dried sufficiently to have a minimal energy loss from storage. The process of mixing the heap, however, led to incorporation of wet outer layers and hence the average moisture content was higher in an average sample of chip. After establishment of the heaps, the temperature rose rapidly and this correlated with a peak in carbon dioxide (CO2) concentration within the heap. A peak in methane (CH4) concentration was also detected in both heaps, though more noticeably in the East Midlands heap after around 55 days. In both instances, the peak CH4 concentration occurred as CO2 concentrations dropped, suggesting that after an active period of aerobic decomposition in the first 2 months of storage, the conditions in the heap became anaerobic. The results from this study suggest that outside wood chip storage is not an efficient method of storing biomass, though this may be location-specific as there are some studies showing lower dry matter losses. It is necessary to explore other methods of harvesting SRC to minimise losses and optimise land use efficiency. Further research is required to detect whether there are fugitive emissions of CH4 from wood chip heaps, as this will compromise the net GHG savings from utilising the biomass stored in this way.

This study explores the use of static chamber boxes to detect whether there are fugitive emissions of greenhouse gases (GHGs) from a willow chip storage heap. The results from the boxes were compared with those from 3-m stainless steel probes inserted into the core of the heap horizontally and vertically at intervals. The results from probes showed that there were increases of carbon dioxide (CO2) concentrations in the heap over the first 10 days after heap establishment, which were correlated with a temperature rise to 60 °C. As the CO2 declined, there was a small peak in methane (CH4) concentration in probes orientated vertically in the heap. Static chambers positioned at the apex of the heap detected some CO2 fluxes as seen in the probes; however, the quantities were small and random in nature. A small (maximum 5 ppm) flux in CH4 occurred at the same time as the probe concentrations peaked. Overall, the static chamber method was not effective in monitoring fluxes from the heap as there was evidence that gases could enter and leave around the edges of the chambers during the course of the experiment. In general, the use of standard (25 cm high) static chambers for monitoring fluxes from wood chip heaps is not recommended.

The excretion of nitrogen (N) in faeces and urine from beef cattle contributes to atmospheric pollution through greenhouse gas and ammonia emissions and eutrophication of land and aquatic habitats through excessive N deposition and nitrate leaching to groundwater. As N excretion by beef cattle is rarely measured directly, it is important to accurately predict losses by utilising a combined knowledge of diet and production parameters so that the effect of dietary changes on the potential environmental impact of beef production systems can be estimated. This study aimed to identify differences between IPCC and more detailed country-specific models in the prediction of N excretion and N losses at a system level and determine how the choice of model influences the interpretation of differences in diet at the system scale. The data used in this study were derived from a farm-scale experimental system consisting of three individual grazing farms, each with a different sward type: a permanent pasture, a high sugar ryegrass monoculture, and a high sugar ryegrass with white clover (~30% groundcover). Data were analysed using a mixed linear model (residual maximum likelihood analysis). The IPCC methods demonstrated significantly lower estimates of N excretion than country-specific models for the first housing period and significantly greater losses for the grazing and second housing periods. The country-specific models enabled prediction of N partitioning to urine and faeces, which is important for estimation of subsequent N losses through the production system, although the models differed in their estimates. Overall, predicted N losses were greater using the IPCC approaches compared to using more detailed country-specific approaches. The outcomes of the present study have highlighted that different models can have a substantial impact on the predicted N outputs and subsequent losses to the environment for pasture-based beef finishing systems, and the importance, therefore, of using appropriate models and parameters.

SummaryThe North Wyke Farm Platform (NWFP) provides data from the field‐ to the farm‐scale, enabling the research community to address key issues in sustainable agriculture better and to test models that are capable of simulating soil, plant and animal processes involved in the systems. The tested models can then be used to simulate how agro‐ecosystems will respond to changes in the environment and management. In this study, we used baseline datasets generated from the NWFP to validate the Soil‐Plant‐Atmosphere Continuum System (SPACSYS) model in relation to the dynamics of soil water content, water loss from runoff and forage biomass removal. The validated model, together with future climate scenarios for the 2020s, 2050s and 2080s (from the International Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES): medium (A1B) and large (A1F1) emission scenarios), were used to simulate the long‐term responses of the system with three contrasting treatments on the NWFP. Simulation results demonstrated that the SPACSYS model could estimate reliably the dynamics of soil water content, water loss from runoff and drainage, and cut biomass for a permanent sward. The treatments responded in different ways under the climate change scenarios. More carbon (C) is fixed and respired by the swards treated with an increased use of legumes, whereas less C was lost through soil respiration with the planned reseeding. The deep‐rooting grass in the reseeding treatment reduced N losses through leaching, runoff and gaseous emissions, and water loss from runoff compared with the other two treatments.

According to the available guidelines, good practices for calculating nitrous oxide (N2O) emission factors (EFs) for livestock excreta and manure application include that sampling duration should be of at least one year after the nitrogen (N) application or deposition. However, the available experimental data suggest that in many cases most emissions are concentrated in the first months following N application. Therefore resources could be better deployed by measuring more intensively during a shorter period. This study aimed to assess the contribution of the N2O flux in the period directly after N application to the annual net emission. We used a database of 100 year-long plot experiments from different excreted-N sources (dung, urine, farmyard manure and slurry) used to derive EFs for the UK and Ireland. We explored different shorter potential measurement periods that could be used as proxies for cumulative annual emissions. The analysis showed that the majority of emissions occur in the first months after application, especially in experiments that i) had urine as the N source, ii) had spring N application, iii) were conducted on fine-textured soils, or iv) showed high annual emissions magnitude. Experiments that showed a smaller percentage of emissions in the first months also had a low magnitude of annual net emissions (below 370 gN2O-N ha-1 year-1), so the impact of measuring during a shorter period would not greatly influence the calculated EF. Accurate EF estimations were obtained by measuring for at least 60 days for urine (underestimation: 7.1%), 120 days for dung and slurry (4.7 and 5.1%) and 180 days for FYM (1.4%). At least in temperate climates, these results are promising in terms of being able to estimate annual N2O fluxes accurately by collecting data for less than 12 months, with significant resource-saving when conducting experiments towards developing country-specific EFs.