Greenhouse gas emissions from cattle dung depositions in two Urochloa forage fields with contrasting biological nitrification inhibition (BNI) capacity.

Grazing-based production systems are a source of soil greenhouse gas (GHG) emissions triggered by excreta depositions. The adoption of Urochloa forages (formerly known as Brachiaria) with biological nitrification inhibition (BNI) capacity is a promising alternative to reduce nitrous oxide (N2O) emissions from excreta patches. However, how this forage affects methane (CH4) or carbon dioxide (CO2) emissions from excreta patches remains unclear. This study investigated the potential effect of soils under two Urochloa forages with contrasting BNI capacity on GHG emissions from cattle dung deposits. Additionally, the N2O and CH4 emission factors (EF) for cattle dung under tropical conditions were determined. Dung from cattle grazing star grass (without BNI) was deposited on both forage plots: Urochloa hybrid cv. Mulato and Urochloa humidicola cv. Tully, with a respectively low and high BNI capacity. Two trials were conducted for GHG monitoring using the static chamber technique. Soil and dung properties and GHG emissions were monitored in trial 1. In trial 2, water was added to simulate rainfall and evaluate GHG emissions under wetter conditions. Our results showed that beneath dung patches, the forage genotype influenced daily CO2 and cumulative CH4 emissions during the driest conditions. However, no significant effect of the forage genotype was found on mitigating N2O emissions from dung. We attribute the absence of a significant BNI effect on N2O emissions to the limited incorporation of dung-N into the soil and rhizosphere where the BNI effect occurs. The average N2O EFs was 0.14%, close to the IPCC 2019 uncertainty range (0.01-0.13% at 95% confidence level). Moreover, CH4 EFs per unit of volatile solid (VS) averaged 0.31 g CH4 kgVS-1, slightly lower than the 0.6 g CH4 kgVS-1 developed by the IPCC. This implies the need to invest in studies to develop more region-specific Tier 2 EFs, including farm-level studies with animals consuming Urochloa forages to consider the complete implications of forage selection on animal excreta based GHG emissions.

Estimation of greenhouse gas emission flux from agricultural lands of Khuzestan province in Iran.

Greenhouse gas emissions and their effects on global warming are one of the serious challenges of developed and developing countries. Investigating the amount of greenhouse gas emissions of different countries makes it possible to determine the share of countries in the production of greenhouse gases. The purpose of this study is to use DAYCENT and DNDC models to estimate the emission rate of methane, nitrous oxide, and carbon dioxide greenhouse gases as well as to estimate the global warming potential in Khuzestan agricultural lands in Iran. For this purpose, the gas sampling was done in rice, wheat, and sugarcane fields using a static chamber, and then the concentration of methane, nitrous oxide, and carbon dioxide was determined by using gas chromatography. In the following, DAYCENT and DNDC models were used to estimate gas emissions and the global warming potential of these gases was estimated. Finally, TOPSIS method was used to prioritize gas emissions. In order to evaluate the modeling accuracy, the statistical indicators of maximum error, root mean square error, determination coefficient, model efficiency, and residual mass coefficient were used. According to the results, the highest measured gas flux was obtained for rice fields at Baghmalek and the lowest for sugarcane in Abadan. The results of DAYCENT model estimation showed that the highest emissions were obtained for methane gas and rice cultivation, and lowest gas emissions were obtained for sugarcane cultivation. The results of DNDC model estimation also showed that the highest flux was determined for nitrous oxide gas in rice cultivation. The results of the estimation of global warming potential also showed that it was the highest in sugarcane cultivation (Shushtar station) and the DAYCENT model, and the lowest was also in wheat cultivation and the DNDC model. The statistical results of the estimation of DAYCENT and DNDC models showed that the DAYCENT model in sugarcane cultivation (Shushtar station) was the most accurate in estimating carbon dioxide gas, and the lowest accuracy was related to the DNDC model and sugarcane cultivation (Shushtar station) in estimating nitrous oxide gas. According to the results of agricultural activities in Khuzestan province, they have made a major contribution to the production of greenhouse gases, which, or the lack of attention to this issue, will have an effect on the future climate of this region.

Environmental and anthropogenic drivers of soil methane fluxes in forests: Global patterns and among-biomes differences.

Forest soils are the most important terrestrial sink of atmospheric methane (CH4 ). Climatic, soil and anthropogenic drivers affect CH4 fluxes, but it is poorly known the relative weight of each driver and whether all drivers have similar effects across forest biomes. We compiled a database of 478 in situ estimations of CH4 fluxes in forest soils from 191 peer-reviewed studies. All forest biomes (boreal, temperate, tropical and subtropical) but savannahs act on average as CH4 sinks, which presented positive fluxes in 65% of the sites. Mixed effects models showed that combined climatic and edaphic variables had the best support, but anthropogenic factors did not have a significant effect on CH4 fluxes at global scale. This model explained only 19% of the variance in soil CH4 flux which decreased with declines in precipitation and increases in temperature, and with increases in soil organic carbon, bulk density and soil acidification. The effects of these drivers were inconsistent across biomes, increasing the model explanation of observed variance to 34% when the drivers have a different slope for each biome. Despite this limited explanatory value which could be related to the use of soil variables calculated at coarse scale (~1 km), our study shows that soil CH4 fluxes in forests are determined by different environmental variables in different biomes. The most sensitive system to all studied drivers were the temperate forests, while boreal forests were insensitive to climatic variables, but highly sensitive to edaphic factors. Subtropical forests and savannahs responded similarly to climatic variables, but differed in their response to soil factors. Our results suggest that the increase in temperature predicted in the framework of climate change would promote CH4 emission (or reduce CH4 sink) in subtropical and savannah forests, have no influence in boreal and temperate forests and promote uptake in tropical forests.

A simple and rapid in situ method for measuring landfill gas emissions and methane oxidation rates in landfill covers.

A newly developed static chamber method with a laser methane detector and a biogas analyser was proposed to measure the landfill gas emissions and methane (CH4) oxidation rates in landfill covers. The method relied on a laser methane detector for measuring CH4 concentration, avoiding gas samplings during test and hence the potential interference of gas compositions inside the chamber. All the measurements could be obtained on site. The method was applied to determine the landfill gas emissions and CH4 oxidation rates in a full-scale loess gravel capillary barrier cover constructed in landfill. Both laboratory calibration and in-situ tests demonstrated that fast (i.e. <20 min) and accurate measurements could be obtained by the proposed method. The method is capable of capturing the significant spatial and temporal variations of the landfill gas emissions and CH4 oxidation rates in landfill site.

Field investigation of temporal variation and diffusion of hydrogen sulfide on waste working face and intermediate landfill cover.

This paper presents the study on the variation, influencing factors and diffusion regularity of hydrogen sulfide (H2S) concentration and surface flux on the working face and intermediate geomembrane cover of a landfill. Field investigations were conducted using static chambers at a large-scale municipal solid waste landfill in Hangzhou, China, from January 2019 to June 2021. The analytical models of H2S transport in the working face and intermediate cover were developed to investigate the surface flux under various conditions. The CALPUFF model was used to demonstrate the diffusion path. The H2S surface flux on the working face ranged from 7.1 × 10-3 to 1.7 mg/m2/h, whereas the range was found to be 1.5 × 10-4 to 0.9 mg/m2/h on the intermediate geomembrane cover. This observation indicated that the geomembrane can reduce H2S emissions. In addition, the H2S surface fluxes at the HDPE GMB seams and near the gas collecting wells were generally 1-2 orders of magnitude larger than that in the intact GMB. The analytical model estimates that the intact GMB exhibits a diffusion coefficient of H2S ranging from 2.7 × 10-11 to 2.2 × 10-10 m2/s. However, the diffusion coefficient increases significantly to a range of 3.3 × 10-11-9.8 × 10-7 m2/s on the GMB seams. According to CALPUFF results, only the H2S diffusion from the working face had areas exceeding the standard concentration.

Spatiotemporal patterns and drivers of stem methane flux from two poplar forests with different soil textures.

In forest ecosystems, the majority of methane (CH4) research focuses on soils, whereas tree stem CH4 flux and driving factors remain poorly understood. We measured the in situ stem CH4 flux using the static chamber-gas chromatography method at different heights in two poplar (Populus spp.) forests with separate soil textures. We evaluated the relationship between stem CH4 fluxes and environmental factors with linear mixed models and estimated the tree CH4 emission rate at the stand level. Our results showed that poplar stems were a net source of atmospheric CH4. The mean stem CH4 emission rates were 97.51 ± 6.21 µg·m-2·h-1 in Sihong and 67.04 ± 5.64 µg·m-2·h-1 in Dongtai. The stem CH4 emission rate in Sihong with clay loam soils was significantly higher (P < 0.001) than that in Dongtai with sandy loam soils. The stem CH4 emission rate also showed a seasonal variation, minimum in winter and maximum in summer. The stem CH4 emission rate generally decreased with increasing sampling height. Although the differences in CH4 emission rates between stem heights were significant in the annual averages, these differences were driven by differences observed in the summer. Stem CH4 emission rates were significantly and positively correlated with air temperature (P < 0.001), relative humidity (P < 0.001), soil water content (P < 0.001) and soil CH4 flux (P < 0.001). At these sites, the soil emitted CH4 to the atmosphere in summer (mainly from June to September) but absorbed CH4 from the atmosphere during the other season. At the stand level, tree CH4 emissions accounted for 2-35.4% of soil CH4 uptake. Overall, tree stem CH4 efflux could be an important component of the forest CH4 budget. Therefore, it is necessary to conduct more in situ monitoring of stem CH4 flux to accurately estimate the CH4 budget in the future.

Dynamic chamber as a more reliable technique for measuring methane emissions from aquatic ecosystems.

Aquatic ecosystems are the largest natural source of atmospheric methane ("CH4") worldwide. However, the current estimation of CH4 emissions from aquatic ecosystems still has extensive uncertainty due to large spatiotemporal variations in CH4 emissions as well as significant uncertainty in measurement methods. In this study, we initially investigated CH4 fluxes from a simulated eutrophic water body by using static chamber method ("SC") during an incubation period of 36 days. Approximately 23 % of the total flux measurements were unsuccessful because they lacked a linear correlation between the accumulation of CH4 concentrations and enclosure time. CH4 fluxes could be achieved for most measurements. However, 5 min after enclosing, the initial CH4 concentrations measured in the chambers were too high (up to 507.4 ppm) to greatly suppress CH4 emissions from the diffusion process. Therefore, a dynamic chamber method ("DC") was developed to overcome the shortcomings of the SC. To achieve the DC, air samples must be continuously collected at the inlet and outlet of the dynamic chamber at fixed flow rates. In contrast to the SC, effective CH4 flux data could be obtained by the DC for each measurement at different frequencies. The DC measured the diel and daily variations in CH4 fluxes and the displayed CH4 emissions from the simulated water were highly irregular. The displayed emissions had variations up to more than two orders of magnitude. These results implied that the SC measured few intermittent fluxes that were difficult to represent the actual CH4 emissions from eutrophic water. The DC developed in this study considers the temporal variations in CH4 emissions from aquatic ecosystems. Thus, the DC is expected to be applicable in the field flux measurements of CH4 as well as other greenhouse gases to reduce emissions uncertainties.

Numerical model for static chamber measurement of multi-component landfill gas emissions and its application.

The quantitative assessment of landfill gas emissions is essential to assess the performance of the landfill cover and gas collection system. The relative error of the measured surface emission of landfill gas may be induced by the static flux chamber technique. This study aims to quantify effects of the size of the chamber, the insertion depth, pressure differential on the relative errors by using an integrated approach of in situ tests, and numerical modeling. A field experiment study of landfill gas emission is conducted by using a static chamber at one landfill site in Xi'an, Northwest China. Additionally, a two-dimensional axisymmetric numerical model for multi-component gas transport in the soil and the static chamber is developed based on the dusty-gas model (DGM). The proposed model is validated by the field data obtained in this study and a set of experimental data in the literature. The results show that DGM model has a better capacity to predict gas transport under a wider range of permeability compared to Blanc's method. This is due to the fact that DGM model can explain the interaction among gases (e.g., CH4, CO2, O2, and N2) and the Knudsen diffusion process while these mechanisms are not included in Blanc's model. Increasing the size and the insertion depth of static chambers can reduce the relative error for the flux of CH4 and CO2. For example, increasing the height of chambers from 0.55 to 1.1 m can decrease relative errors of CH4 and CO2 flux by 17% and 18%, respectively. Moreover, we find that gas emission fluxes for the case with positive pressure differential (∆Pin-out) are greater than that of the case without considering pressure fluctuations. The Monte Carlo method was adopted to carry out the statistical analysis for quantifying the range of relative errors. The agreement of the measured field data and predicted results demonstrated that the proposed model has the capacity to quantify the emission of landfill gas from the landfill cover systems.

Divergent consequences of different biochar amendments on carbon dioxide (CO2) and nitrous oxide (N2O) emissions from the red soil.

Climate change due to greenhouse gas (GHG) emissions is one of the global environmental matters of the 21st century. Biochar (BC) amendments have been proposed as a potential solution for improving soil quality and to mitigate GHGs emissions. Therefore, we evaluated the influence of different BCs on soil CO2 and N2O emissions in an outdoor pot experiment. The soil was mixed with three different types of BCs; bamboo, hardwood, and rice straw BCs as BB, BH, and BR, respectively, and control as B0 with four levels (0, 5, 20, and 80 g kg-1 of soil). Gas samples were collected on a bi-monthly basis for six months. A polyvinyl chloride (PVC) static chamber was placed on each replicate to collect the gas samples at 15, 30, 45, and 60 min, respectively. Compared to B0, the lowest cumulative N2O emissions were observed in BH80 (11%) followed by BH20, BH5, and BR80. However, for cumulative CO2 emissions, B0 and BC treatments showed no significant differences except for BB80 (>11%) and BB5 (<2%). BC type and level both had a significant (P < 0.001) impact on the cumulative N2O emissions with a significant interaction (P < 0.001). However, cumulative CO2 emissions were unaffected by BC type but BC level showed a significant influence on cumulative CO2 emissions (P < 0.05) and there was a significant (P < 0.001) interaction between the BC type and level on cumulative CO2 emissions. Overall, higher doses of BR and BB showed a pronounced effect on soil pH over BH. The soil pH and moisture showed a negative correlation with N2O emissions whereas soil temperature showed a positive correlation with the cumulative fluxes of N2O. Our results demonstrate that BC incorporation to soil may help to mitigate GHGs emissions but its influence may vary with BC type and level under different conditions and soil type.

Nitrous oxide fluxes of a boreal abandoned pasture do not significantly differ from an adjacent natural bog despite distinct environmental conditions.

Land-use conversion of pristine boreal peatlands for agricultural purposes is an ongoing process and projected to become more intensive with rising population growth and increased demands for food production. However, agricultural use of peatlands affects the production and emission of nitrous oxide (N2O), a very potent greenhouse gas currently gaining more attention in the global assessment of greenhouse gases. While the intensity of N2O emissions depends on a range of environmental factors, including hydrological parameters, temperature and the availability of nitrogen in soils, key driving processes remain poorly understood. In order to understand the effects of land-use change on the peatland ecosystem, we quantified N2O fluxes under different land-use in a comparative study between a natural bog and an adjacent abandoned pasture in Newfoundland, Canada. We conducted in situ gas flux measurements using the static chamber method over five growing seasons. In addition, we measured photosynthetic rates and environmental parameters, namely soil temperature and moisture, water table and concentrations of total nitrogen and dissolved organic carbon in pore waters. According to previous studies, we hypothesized higher N2O emissions from the abandoned pasture due to drainage compared to the natural bog. However, despite significant differences of environmental parameters and photosynthetic rates, we found no significant difference of N2O fluxes between the two sites. We argue that N2O production at the abandoned pasture was inhibited due to exhaustion of plant-available nitrogen as a result of increased gross primary production compared to the natural bog. We conclude that the effect of drainage and fertilization on N2O fluxes during the growing season was superposed by vegetation composition change effects at the abandoned pasture, leading to similar N2O fluxes at both sites.

Soil CO2 emissions from summer maize fields under deficit irrigation.

Irrigation practice is one of the main factors affecting soil carbon dioxide (CO2) emission from croplands and therefore on global warming. As a water-saving irrigation practice, the deficit irrigation has been widely used in summer maize fields and is expected to adapt to the shortage of water resources in Northwest China. In this study, we examined the impacts of deficit irrigation practices on soil CO2 emissions through a plot experiment with different irrigation regimes in a summer maize field in Northwest China. The irrigation regimes consisted of three irrigation treatments: deficit irrigation treatments (T1: reduce the irrigation amount by 20%, T2: reduce the irrigation amount by 40%) and full irrigation (T0) treatments. The results showed that the soil CO2 cumulative emissions with T1 and T2 were decreased by 9.8% (p < 0.05) and 14.3% (p < 0.05), respectively, compared with T0 treatment (1365.3 kg-C ha-1). However, there were no significant differences between T1 and T2 treatments (p > 0.05). Soil CO2 fluxes with different irrigation treatments showed significant correlations with soil moisture (p < 0.001) and soil temperature (p < 0.05). It was also observed that summer maize yields with T1 and T2 treatments were reduced by 4.9% (p > 0.05) and 30.9% (p < 0.05), compared with T0 (34.3 t ha-1), respectively. The findings demonstrate that the deficit irrigation treatment (T1) resulted in a considerable decrease in soil CO2 emissions without impacting the summer maize yields significantly. The results could be interpreted to develop better irrigation management practices aiming at reducing soil CO2 emissions, saving water, and ensuring crop yield in the summer maize fields in Northwest China.

Characteristics of methane emissions in the Living Water Garden in Chengdu City from 2012 to 2017.

CH4 flux measured by a portable chamber using an infrared analyzer was compared with the flux by static chamber measurement for CW at 13 different sites from May 2012 to May 2017 in the Living Water Garden (LWG) in Chengdu, Sichuan Province, China, over 4 timescales (daily, monthly, seasonal, and annual). During the measurement period, a total of 1443 data were collected. CH4 fluxes were measured using the portable chamber method and the results showed that the annual mean and median CH4 flux values in the LWG were 17.4 mg m-2 h-1 and 6.2 mg m-2 h-1, respectively, ranging from - 19.7 to 98.0 mg m-2 h-1. Cumulative CH4 emissions for LWG ranged from - 0.17 to 0.86 kg m-2 year-1. Global warming potential (GWP, 25.7 kg CO2eq m-2 year-1) was at a high level, which means that the LWG was a source of CH4 emissions. Significant temporal variations on the 4 timescales were observed. And the asymmetry of measurement uncertainty of CH4 flux increases with the timescale. Although the total mean CH4 flux measured by the portable chamber method was 42.1% lower than that of the static chamber method, the temporal variation trends of CH4 flux were similar. The uncertainty of CH4 flux measured in portable chamber was more symmetrical than that in static chamber. These results suggest that the portable chamber method has considerable value as a long-term measurement method for CH4 flux temporal variations.

Optimized methods for diffusive greenhouse gas flux analyses in inland waters.

Inland waters are considered hotspots of greenhouse gas (GHG) emissions and have been extensively researched. Static chamber (STAT) and thin boundary layer (BLE) are two commonly used methods for analyzing diffusive GHG emissions from inland waters. However, the STAT method is often disturbed by GHG bubbles; meanwhile, many kinds of headspace gas are used in the BLE method, but the differences between their diffusive GHG emission analysis results are not understood. In this study, the chamber in the STAT method was modified to combat the disturbances from GHG bubbles, and the typically used gases for the BLE method, namely, pure nitrogen, air, and filtered air, were comparatively studied. Results demonstrated that the modified chamber could effectively prevent the invasion of GHG bubbles; it increased the success rate from 67 to 90% in the field test, with no obvious impacts on the results of the GHG emission analyses. The use of air and filtered air in the BLE method yielded the lower values of GHG emissions relative to pure nitrogen, and this finding was potentially attributed to the inhibition effects of the residual GHGs and high humidity in air and filtered air on the extraction of diffusive GHGs from the surface water. This study improved the commonly used methods for diffusive GHG emission analysis, and the current findings are beneficial to the study of GHG emissions from inland waters.

Occurrence and fate of methane leakage from cut and buried abandoned gas wells in the Netherlands.

Methane leakage caused by well integrity failure was assessed at 28 abandoned gas wells and 1 oil well in the Netherlands, which have been plugged, cut and buried to below the ground surface (≥3 mbgl). At each location, methane concentrations were thoroughly scanned at the surface. A static chamber setup was used to measure methane flow rates from the surface as well as from 1 m deep holes drilled using a hand auger. An anomalously high flow rate from 1 m depth combined with isotopic confirmation of a thermogenic origin revealed ongoing leakage at 1 of the 29 wells (3.4%), that had gone undetected by surficial measurements. Gas fluxes at the other sites were due to shallow production of biogenic methane. Detailed investigation at the leaking well (MON-02), consisting of 28 flux measurements conducted in a 2 × 2 m grid from holes drilled to 1 and 2 m depth, showed that flux magnitude was spatially heterogeneous and consistently larger at 2 m depth compared to 1 m. Isotopic evidence revealed oxidation accounted for roughly 25% of the decrease in flux towards the surface. The estimated total flux from the well (443 g CH4 hr-1) was calculated by extrapolation of the individual flow rate measurements at 2 m depth and should be considered an indicative value as the validity of the estimate using our approach requires confirmation by modelling and/or experimental studies. Together, our findings show that total methane emissions from leaking gas wells in the Netherlands are likely negligible compared to other sources of anthropogenic methane emissions (e.g. <1% of emissions from the Dutch energy sector). Furthermore, subsurface measurements greatly improve the likelihood of detecting leakage at buried abandoned wells and are therefore essential to accurately assess their greenhouse gas emissions and explosion hazards.

[Water-Air Interface CO2 Exchange Flux of Typical Lakes in a Mountainous Area of the Western Chongqing and Their Influencing Factors].

To examine the mountainous lake CO2 evasion in Southwest China, partial pressures of carbon dioxide[p(CO2)] and the CO2 exchange flux[F(CO2)] via the water-air interface of nine mountainous lakes in Chongqing, China, have been studied in summer using the thin boundary layer model (TBL) and floating chambers. Key water quality parameters were concomitantly measured. The results indicate that the pCO2 in the mountainous lakes in western Chongqing ranges from 2.1 to 45.0 Pa, with a mean value of (18.1±12.1) Pa. The mean CO2 fluxes calculated by the TBL model and chamber method are (-8.0±2.9), (-3.4±3.6), and (-7.1±22.3) mmol·(m2·d)-1, respectively. The p(CO2) and F(CO2) have positive correlations with the wind speed and ORP but negative correlations with the pH. Our study indicates that mountainous lakes are atmospheric sinks of CO2 and the TBL model should be cautiously adopted.

Effects of storage time and temperature on greenhouse gas samples in Exetainer vials with chlorobutyl septa caps.

Measurement of greenhouse gas (GHG) flux using static chamber methods typically occurs immediately following sample collection. However, situations may arise requiring sample storage prior to analysis by gas chromatography. The objective of this study was to determine effects of storage time and temperature on carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) concentrations in vials containing "low" and "high" concentrations of certified standards. Samples were stored for 3, 7, 14, 28, and 84 days at four storage temperatures: room temperature, 25 °C, 4 °C, and -10 °C. Results indicated low and high concentration standards were not impacted by sample storage up to 28 days at any storage temperature. After 84 days, CO2 concentrations were 0.6-14.4% lower than expected while CH4 concentrations were up to 22% greater than expected. Results from future studies will allow for further refinement of scientifically supported guidance regarding appropriate storage temperature and time of GHG samples. •Few studies have examined impacts of storage time and temperature on GHG samples retained in traditional septa-capped vials.•Effects of storage time and temperature on GHG samples were examined.•Based on this study, GHG samples can be stored for up to 28 days at temperatures ranging from -10 °C to 25 °C.

Bi-directional soil/atmosphere N2 O exchange over two mown grassland systems with contrasting management practices.

Nitrous oxide (N2 O) fluxes from soil under mown grassland were monitored using static chambers over three growing seasons in intensively and extensively managed systems in Central Switzerland. Emissions were largest following the application of mineral (NH4 NO3 ) fertilizer, but there were also substantial emissions following cattle slurry application, after grass cuts and during the thawing of frozen soil. Continuous flux sampling, using automatic chambers, showed marked diurnal patterns in N2 O fluxes during emission peaks, with highest values in the afternoon. Net uptake fluxes of N2 O and subambient N2 O concentrations in soil open pore space were frequently measured on both fields. Flux integration over 2.5 years yields a cumulated emission of +4.7 kgN2 O-N ha-1 for the intensively managed field, equivalent to an average emission factor of 1.1%, and a small net sink activity of -0.4 kg N2 O-N ha-1 for the unfertilized system. The data suggest the existence of a consumption mechanism for N2 O in dry, areated soil conditions, which cannot be explained by conventional anaerobic denitrification. The effect of fertilization on greenhouse gas budgets of grassland at the ecosystem level is discussed.

Optimum sampling time and frequency for measuring N2O emissions from a rain-fed cereal cropping system.

Annual cumulative nitrous oxide (N2O) emissions from soil have historically been calculated from intermittent data measured manually via the static chamber method. The temporal variability in emissions, both diurnally and between days, introduces uncertainty into the up-scaling of static chamber data. This study assessed the most appropriate time of the day to sample and the best sampling frequency to ensure reliable estimates of annual cumulative emissions. Sub-daily N2O emissions were measured using automatic gas sampling chambers over three years in a sub-tropical cereal crop system. The sub-daily dataset was divided into eight time periods per day to assess the best sampling time of the day. Daily mean N2O emissions were subsampled from the dataset to simulate different sampling frequencies, including pre-set and rainfall-based scenarios. Annual cumulative N2O emissions were calculated for these scenarios and compared to the 'actual' annual cumulative emissions. The results demonstrated that manual sampling between mid-morning (09:00) and midday (12:00), and late evening (21:00) and midnight (24:00) best approximated the daily mean N2O emission. Factoring in the need to sample during daylight hours, gas sampling from mid-morning to midday was the most appropriate sampling time. Overall, triweekly sampling provided the most accurate estimate (± 4% error) of annual cumulative N2O emissions, but was undesirable due to its labour intensive high sampling frequency. Weekly sampling with triweekly sampling in the two weeks following rainfall events was the most efficient sampling schedule, as it had similar accuracy (± 5% error) to the triweekly sampling, the smallest variability in outcomes and approximately half the sampling times of triweekly sampling. Inter-annual rainfall variability affected the accuracy and variability of estimations of annual cumulative emissions, but did not affect the overall trends in sampling frequency accuracy. This study demonstrated that intermittent samplings are capable of estimating the annual cumulative N2O emissions satisfactorily when timed appropriately.