Measuring nitrous oxide emissions from conventional and controlled release fertilisers in south-east Queensland pineapple production

Nitrous oxide (N2O) is a potent greenhouse gas with a global warming potential 298 times higher than carbon dioxide. Soils are a natural source of N2O, contributing 65% of global emissions. This paper is the first in Australia to measure and compare N2O emissions from pre-plant controlled release (CR) and conventional granular (CV) fertilisers in pineapple production using static PVC chambers to capture N2O emissions. Farm 1 cumulative emissions from the CR fertiliser were 3.22 kg ha-1 compared to 6.09 kg ha-1 produced by the CV. At farm 2 the CV blend emitted 2.36 kg ha-1 in comparison to the CR blend of 2.92 kg ha-1. Daily N2O flux rates showed a relationship of direct response to rainfall and soil moisture availability. High emissions were observed for wheel tracks where increased N2O emissions may be linked to soil compaction and waterlogging that creates anaerobic conditions after rain events. Emission measurements over three months highlighted the inconsistencies found in other studies relative to reducing emissions through controlled release nitrogen. More investigations are required to verify the benefits associated with controlled release fertiliser use in pineapples, placement and seasonal timing to address N2O emissions in pineapples.

Quantifying nitrous oxide emissions from sugarcane cropping systems : Optimum sampling time and frequency

Nitrous oxide (N2O) emissions from soil are often measured using the manual static chamber method. Manual gas sampling is labour intensive, so a minimal sampling frequency that maintains the accuracy of measurements would be desirable. However, the high temporal (diurnal, daily and seasonal) variabilities of N2O emissions can compromise the accuracy of measurements if not addressed adequately when formulating a sampling schedule. Assessments of sampling strategies to date have focussed on relatively low emission systems with high episodicity, where a small number of the highest emission peaks can be critically important in the measurement of whole season cumulative emissions. Using year-long, automated sub-daily N2O measurements from three fertilised sugarcane fields, we undertook an evaluation of the optimum gas sampling strategies in high emission systems with relatively long emission episodes. The results indicated that sampling in the morning between 09:00–12:00, when soil temperature was generally close to the daily average, best approximated the daily mean N2O emission within 4–7% of the ‘actual’ daily emissions measured by automated sampling. Weekly sampling with biweekly sampling for one week after >20 mm of rainfall was the recommended sampling regime. It resulted in no extreme (>20%) deviations from the ‘actuals’, had a high probability of estimating the annual cumulative emissions within 10% precision, with practicable sampling numbers in comparison to other sampling regimes. This provides robust and useful guidance for manual gas sampling in sugarcane cropping systems, although further adjustments by the operators in terms of expected measurement accuracy and resource availability are encouraged. By implementing these sampling strategies together, labour inputs and errors in measured cumulative N2O emissions can be minimised. Further research is needed to quantify the spatial variability of N2O emissions within sugarcane cropping and to develop techniques for effectively addressing both spatial and temporal variabilities simultaneously.

Review of greenhouse gas emissions from the storage and land application of farm dairy effluent

The amounts of farm dairy effluent stored in ponds and irrigated to land have steadily increased with the steady growth of New Zealand's dairy industry. About 80% of dairy farms now operate with effluent storage ponds allowing deferred irrigation. These storage and irrigation practices cause emissions of greenhouse gases (GHG) and ammonia. The current knowledge of the processes causing these emissions and the amounts emitted is reviewed here. Methane emissions from ponds are the largest contributor to the total GHG emissions from effluent in managed manure systems in New Zealand. Nitrous oxide emissions from anaerobic ponds are negligible, while ammonia emissions vary widely between different studies, probably because they depend strongly on pH and manure composition. The second-largest contribution to GHG emissions from farm dairy effluent comes from nitrous oxide emissions from land application. Ammonia emissions from land application of effluent in New Zealand were found to be less than those reported elsewhere from the application of slurries. Recent studies have suggested that New Zealand's current GHG inventory method to estimate methane emissions from effluent ponds should be revised. The increasing importance of emissions from ponds, while being a challenge for the inventory, also provides an opportunity to achieve mitigation of emissions due to the confined location of where these emissions occur. © 2015 © 2015 The Royal Society of New Zealand.

Validation of PigBal model predictions for pig manure production

PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and –0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal’s capabilities for more accurately assessing nutrient loads. However, PigBal’s satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions.

Nitrogen use efficiency in summer sorghum grown on clay soils

Nitrogen fertilizer inputs dominate the fertilizer budget of grain sorghum growers in northern Australia, so optimizing use efficiency and minimizing losses are a primary agronomic objective. We report results from three experiments in southern Queensland sown on contrasting soil types and with contrasting rotation histories in the 2012-2013 summer season. Experiments were designed to quantify the response of grain sorghum to rates of N fertilizer applied as urea. Labelled 15N fertilizer was applied in microplots to determine the fate of applied N, while nitrous oxide (N2O) emissions were continuously monitored at Kingaroy (grass or legume ley histories) and Kingsthorpe (continuous grain cropping). Nitrous oxide is a useful indicator of gaseous N losses. Crops at all sites responded strongly to fertilizer N applications, with yields of unfertilized treatments ranging from 17% to 52% of N-unlimited potential. Maximum yields ranged from 4500 (Kupunn) to 5450 (Kingaroy) and 8010 (Kingsthorpe) kg/ha. Agronomic efficiency (kg additional grain produced/kg fertilizer N applied) at the optimum N rate on the Vertosol sites was 23 (80 N, Kupunn) to 25 (160N, Kingsthorpe), but 40-42 on the Ferrosols at Kingaroy (70-100N). Cumulative N2O emissions ranged from 0.44% (Kingaroy legume) to 0.93% (Kingsthorpe) and 1.15% (Kingaroy grass) of the optimum fertilizer N rate at each site, with greatest emissions from the Vertosol at Kingsthorpe. The similarity in N2O emissions factors between Kingaroy and Kingsthorpe contrasted markedly with the recovery of applied fertilizer N in plant and soil. Apparent losses of fertilizer N ranged from 0-5% (Ferrosols at Kingaroy) to 40-48% (Vertosols at Kupunn and Kingsthorpe). The greater losses on the Vertosols were attributed to denitrification losses and illustrate the greater risks of N losses in these soils in wet seasonal conditions.

Validation of PigBal model predictions for pig manure production

PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and -0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal's capabilities for more accurately assessing nutrient loads. However, PigBal's satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions. © CSIRO 2016.