Micrometeorological Techniques Research Articles

A pre-whitening with block-bootstrap cross-correlation procedure for temporal alignment of data sampled by eddy covariance systems

The eddy covariance (EC) method is a standard micrometeorological technique for monitoring the exchange rate of the main greenhouse gases across the interface between the atmosphere and ecosystems. One of the first EC data processing steps is the temporal alignment of the raw, high frequency measurements collected by the sonic anemometer and gas analyser. While different methods have been proposed and are currently applied, the application of the EC method to trace gases measurements highlighted the difficulty of a correct time lag detection when the fluxes are small in magnitude. Failure to correctly synchronise the time series entails a systematic error on covariance estimates and can introduce large uncertainties and biases in the calculated fluxes. This work aims at overcoming these issues by introducing a new time lag detection procedure based on the assessment of the cross-correlation function (CCF) between variables subject to (i) a pre-whitening based on autoregressive filters and (ii) a resampling technique based on block-bootstrapping. Combining pre-whitening and block-bootstrapping facilitates the assessment of the CCF, enhancing the accuracy of time lag detection between variables with correlation of low order of magnitude (i.e. lower than -1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-1$$\\end{document}) and allowing for a proper estimate of the associated uncertainty. We expect the proposed procedure to significantly improve the temporal alignment of the EC time-series measured by two physically separate sensors, and to be particularly beneficial in centralised data processing pipelines of research infrastructures (e.g. the Integrated Carbon Observation System, ICOS-RI) where the use of robust and fully data-driven methods, like the one we propose, constitutes an essential prerequisite.

Growing Importance of Micro-Meteorology in the New Power System: Review, Analysis and Case Study

With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides review including the relevant micro-meteorological techniques such asbservation, assimilation andumerical techniques, as well as artificial intelligence, presenting a relatively complete overview ofhe most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systemss analyzed inix different forms of power generationnd three typical scenariosf different stages in theower system, as well as integrated energy systemsnd disaster prevention and reduction. Finally, aase study in China is provided. This case takes wind power prediction as an example in aower system to compare the performance whenpplying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial–temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to theower system to some extent.

Measurement of Long-Term CH4 Emissions and Emission Factors from Beef Feedlots in Australia

One of the major challenges for the Australian feedlot and meat sectors is to have accurate and robust long-term greenhouse gas (GHG) emissions data. Long-term measurements of methane (CH4) emissions (2015–2017) were made at two Australian beef feedlots having different climates, cattle types, and management practices. Emissions were measured using the inverse-dispersion model (IDM) micrometeorological technique, using CH4 concentrations measured at the feedlots with a closed-path Fourier transform infrared spectroscopic technique (CP-FTIR). The emissions data were used to evaluate methods used by the Department of Climate Change, Energy, the Environment and Water to estimate CH4 emissions from feedlots in Australian national inventory calculations. Expressed as a CH4 yield (emissions per unit dry matter intake, DMI), the two feedlots had emissions of 13.1 and 18.9 g CH4 kg−1 DMI. The lower-emitting feedlot had emissions that were 30% lower than the national inventory calculations based on feed intakes, while the second feedlot had emissions that were similar to the inventory calculations. The accurate quantification of emissions from feedlots, as demonstrated as part of this study, is important for validating the national accounting methods and therefore the sector’s GHG emissions profile.

Long-term onsite monitoring of a sewage sludge drying pan finds methane emissions consistent with IPCC default emission factor

As the wastewater sector moves towards achieving net zero greenhouse gas (GHG) emissions, quantifying and understanding fugitive emissions from various sewage treatment steps is crucial for developing effective GHG abatement strategies. Methane (CH4) emissions from a sludge drying pan (SDP) were measured at a wastewater treatment plant in Australia for more than a year, using a micrometeorological technique paired with open-path lasers. The emission rate was tightly associated with sludge additions, climatology, and operational processes. The mean emission rate during the 90 weeks after initial sludge addition was 2.3 (± 0.8) g m−2 d−1, with cumulative emissions of approximately 32 t of CH4. A dynamic temporal pattern of emissions was observed, highlighting the importance of continuous (or near-continuous) measurements for quantifying SDP emissions. A Methane Correction Factor (MCF) expressed as a fraction of the measured chemical oxygen demand of the sludge, was determined to be 0.17 after 63 weeks (the median operational cycle duration at the facility). This is broadly consistent with, albeit slightly less than, the IPCC default value of 0.2 for shallow anaerobic lagoons. These emission measurements will support wastewater utilities that employ open air sludge drying processes to develop effective GHG abatement strategies.

Evapotranspiration estimates of soybean using surface renewal: Comparison with crop coefficient approach

Evapotranspiration (ET) is widely considered the main consumptive water use in agricultural production and its accurate determination enables crop producers to make informed decisions. Field experiments were conducted in KwaZulu-Natal, South Africa to estimate soybean ET from sensible and latent heat flux obtained using the surface renewal (SR) method. Two versions of the SR method (SR2) were used. One version combines SR analysis with Monin-Obukhov similarity theory (MOST), hereinafter referred to as SRMOST. The other is a combination of SR analysis and dissipation theory (DT) referred to as SRDT. The ET estimated using SRMOST and SRDT (ETSRMOST and ETSRDT respectively) were compared to the ET obtained using the standard crop coefficient (Kc) approach (ETKc). During flowering, pod formation and seed filling, both SRMOST and SRDT methods slightly overestimated ET obtained using Kc approach with an average normalised root mean square error (NRMSE) of 23.4% and an average normalised mean absolute error (NMAE) of 10.1% for SRMOST and 21.7 and 9.4% for SRDT respectively. During senescence and at maturity, SRMOST and SRDT slightly underestimated ET compared to Kc approach. The average statistical measures for SRMOST were NRMSE = 21.0% and NMAE = 9.2%. Correspondingly, the statistics for SRDT were 17.5 and 7.1% respectively. Both SR2 methods estimated the minimum ET more accurately compared to the maximum. The SRDT method was more in agreement with Kc approach. Surface renewal is robust, less expensive than other micrometeorological techniques and a reliable method for deriving evapotranspiration of soybean when crop coefficients are problematic.

Quantification of methane emitted by ruminants: a review of methods.

The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.

Long-term variability in N2O emissions and emission factors for corn and soybeans induced by weather and management at a cold climate site

Nitrous oxide (N2O) emissions are highly variable in space and time due to the complex interplay between soil, management practices and weather conditions. Micrometeorological techniques integrate emissions over large areas at high temporal resolution. This allows identification of causes of intra- and inter-annual variability of N2O emissions and development of robust emission factors (EF). Here, we investigated factors responsible for variability in N2O emissions during growing and non-growing seasons of corn and soybeans grown in an imperfectly drained silt loam soil, in Ontario, Canada. We used quasi-continuously (at half-hourly to hourly intervals) N2O fluxes measured via the flux-gradient technique over 11 years for corn and 5 years for soybeans and evaluated the uncertainty of default IPCC and Canada-specific EFs. In the growing season, emissions were controlled by soil nitrate content, soil moisture and temperature in the fertilized corn, while moisture and temperature regulated N2O emissions in the unfertilized soybeans. In the non-growing season, nitrogen (N) input from the crop residue did not affect the emissions, pointing to freeze-thaw cycles as mechanisms for enhanced N2O emissions. The non-growing season contribution to annual emissions was 38% in corn and 43% in soybeans. On average, annual emissions were 2.6-fold higher in corn than soybeans. Observed mean N2O EFs were 0.84% (0.12–2.02%) for growing season and 1.69% (0.29–7.32%) for yearly emissions. The growing season EF derived from long-term N2O emissions was 0.9 ± 0.14%. The interannual variability in N2O emissions and EFs can be attributed to management practices and annual weather variability. The default IPCC approach based on overall N input had poorer performance in predicting annual N2O emissions compared to the current Canadian methodology, which includes management and environmental factor in addition to N inputs. The observed emissions were further evaluated with a newly developed growing season N2O emission prediction approach for Canada. However, performance of the approach was poorer than IPCC or the current national Canadian approach. Additional tests of the new national methodology are recommended as well as consideration of non-growing season emissions.

Long-term monitoring of deficit irrigation regimes on citrus orchards in Sicily

The study aims to identify the responses of citrus orchards (C. sinensis (L.) Osbeck), grown under typical Mediterranean climatic conditions, to deficit irrigation (DI) regimes applied over more than a decade (2010-2020). In particular, the DI regimes were declined at the study site in terms of sustained deficit irrigation, regulated deficit irrigation, partial drying of the root-zone, with increasing severity of the water deficit, from 25% to 50% of the crop evapotranspiration, using surface and sub-surface micro-irrigation techniques. Long-term monitoring was set up for identifying the main processes acting at the soil-plant-atmosphere continuum (SPAC) level through direct in situ measurements of mass and energy fluxes (i.e., via micrometeorological technique) and the estimation of ETc and transpiration fluxes (i.e., via sap flow method), and the soil-plant-water processes (via geoelectrical techniques). In addition, the main physiological, qualitative, and quantitative parameters were evaluated since the beginning of the experiment. The results of the long-term experiment demonstrated the great adaptability of the crop species to sustain even the highest water reductions without substantial alterations of the main marketable productive and qualitative characteristics, evidencing the importance of controlling the SPAC dynamics for correctly applying the water restriction regimes.

Perennial grain crops reduce N2O emissions under specific site conditions

Perennial grain crops represent a novel hybrid between annually harvested grain crops and perennial forage crops, which are seeded once and grow for multiple subsequent seasons. Previous research has shown comparatively reduced nitrous oxide (N2O) emissions from perennial forage crops relative to annual grain crops; however, the effect of perennial grain cropping on N2O emissions is unclear. We quantified field N2O emissions along an experimental continuum of perenniality (perennial forage, perennial grain, fall grain, spring grain and fallow) established at two sites within Alberta, Canada with contrasting soils: luvisolic at the Breton site and chernozemic at the Edmonton site. We used static chambers and a micrometeorological technique based on an open-path Fourier-transform infrared gas sensor (OP-FTIR). Perennial grain crops reduced cumulative N2O emissions at the Breton site by 60% and 94% in years two and three of the study, respectively (Ps < 0.0001). Conversely, no reduction in N2O emissions by the perennial grain crop relative to the annual crop was evident at the Edmonton site. Correlation analyses encompassing both sites revealed that the average root density from 0 to 60 cm was negatively correlated with soil available nitrogen (N) (0–15 cm depth) in years one (Ps < 0.01) and two (Ps < 0.05). Moreover, in year two, root density was negatively correlated with cumulative N2O emissions, specifically at the Breton site (P < 0.01). Results suggest that the enhanced root density of perennial crops reduced soil N availability at the Breton site, which translated into reduced cumulative N2O emissions in year two. Notably, increased root density did not correlate with reduced N2O emissions at the Edmonton site, suggesting that factors such as increased soil clay and carbon content in the Chernozemic soil overrode crop controls on N2O emission. Further, OP-FTIR measurements at the Breton site were in general agreement with static chamber measurements, which collectively informed that the bulk reduction in cumulative N2O emissions from the perennial grain plots occurred during spring thaw. Overall, the ability for perennial cereal grain crops to reduce N2O emissions relative to annual crops was site-specific.

Critical Observations of Gaseous Elemental Mercury Air‐Sea Exchange

AbstractAir‐sea exchange of gaseous elemental mercury (Hg0) is not well constrained, even though it is a major component of the global Hg cycle. Lack of Hg0 flux measurements to validate parameterizations of the Hg0 transfer velocity contributes to this uncertainty. We measured the Hg0 flux on the Baltic Sea coast using micrometeorological methods (gradient‐based and relaxed eddy accumulation [REA]) and also simulated the flux with a gas exchange model. The coastal waters were typically supersaturated with Hg0 (mean ± 1σ = 13.5 ± 3.5 ng m−3; ca. 10% of total Hg) compared to the atmosphere (1.3 ± 0.2 ng m−3). The Hg0 flux calculated using the gas exchange model ranged from 0.1–1.3 ng m−2 h−1 (10th and 90th percentile) over the course of the campaign (May 10–June 20, 2017) and showed a distinct diel fluctuation. The mean coastal Hg0 fluxes determined with the two gradient‐based approaches and REA were 0.3, 0.5, and 0.6 ng m−2 h−1, respectively. In contrast, the mean open sea Hg0 flux measured with REA was larger (6.3 ng m−2 h−1). The open sea Hg0 flux indicated a stronger wind speed dependence for the Hg0 transfer velocity compared to commonly used parameterizations. Although based on a limited data set, we suggest that the wind speed dependence of the Hg0 transfer velocity is more consistent with gases that have less water solubility than CO2 (e.g., O2). These pioneering flux measurements using micrometeorological techniques show that more such measurements would improve our understanding of air‐sea Hg exchange.

Independent estimation of sensible and latent fluxes in a vineyard using improved surface renewal analysis

Turbulent fluxes are key components of surface energy balance. Micrometeorological techniques, such as eddy covariance (EC), are commonly used to estimate sensible (H) and latent (LE) heat fluxes, because they provide direct measurements and do not interfere with the normal crop canopy development. However, EC has technical difficulties, strict size, and surface homogeneity requirements and is relatively expensive. Surface renewal analysis (SRA) is a promising alternative for turbulent flux estimation, because it is more economical, has less-stringent fetch requirements, and can be deployed in heterogeneous canopies or markedly sloped surfaces. Castellvi (SRACast) presented a methodology to estimate H using SRA, avoiding the high-frequency wind speed records that are necessary for determining stability and friction velocity, which are then used to calibrate the α parameter (a factor that corrects the nonuniform heating of an air parcel). Instead, an iterative procedure using wind speed recorded using a simple cup anemometer can be used. Here, we estimated sensible and latent heat fluxes and latent heat flux as residual from the energy–balance equation using SRACast during January 2018 and compared the results with EC measurements in a trilled vineyard (heterogeneous canopy), in Pirque, Santiago de Chile. Values of H and LE through SRACast present a high agreement with EC, with slopes (b) of 1.11 and 0.88 and coefficients of determination (R2) of 0.97 and 0.89, respectively. LEres_SRA showed values of 1.60 and 0.80 for b and R2, respectively. Energy balance closure was slightly better for SRA than for EC (b, 0.73 and 0.71; R2, 0.94 and 0.95), proving to be a reasonably good and simpler alternative for turbulent flux estimation.

Water Saving Strategies in Mediterranean Areas

Mediterranean climate is associated with summer water scarcity and, consequently, with a general susceptibility to erosion, degradation, and desertification. Thin soils, with low water storage capacity, develop in slopes where all main factors for erosion can at its worst. The need for wise irrigation is crucial for human activities. Plant adaptation includes stomatal closure as a strategy to reduce water use improving plant survival, while reducing photosynthesis and control of leaf temperature. Other strategies at leaf level include reducing radiation interception and increasing sensible heat diffusion, for instance by developing small leaf size, high leaf reflectance and adapted positions towards sunlight. Another order of survival strategies to cope with summer water scarcity concerns the increase of water uptake at root level and hydraulic lift or water redistribution. Finally, irrigation efficiency and evapotranspiration efficiency also should be optimised. Several experiments were performed on olive orchards under the harsh summer conditions of South East Portugal. The results were consistent in several aspects related to water uptake: colonization of the inter-row space, qualitative and quantitative importance of hydraulic redistribution and water balance estimates from soil water content versus plant water use measured by a micrometeorological technique. In orchards under deficit irrigation, analysed in same study, water use was also quantified and parameters of stress coefficients functions were critically analysed.

Ammonia, methane and nitrous oxide emissions from furrow irrigated cotton crops from two nitrogen fertilisers and application methods

• Urea broadcast and fertigation were applied at a commercial irrigated cotton farm. • Gas emissions were measured by micrometeorological technique and OP-FTIR technique. • NH 3 flux from anhydrous NH 3 was 24% higher than broadcasting urea with irrigation. • Daily fluxes of CH 4 and N 2 O were both negative following both fertilisation events. Abstract Agricultural systems use nitrogen (N) fertilizers to improve crop nutrition and yield, but applied N can negatively impact the environment and human health due to the gases emitted during and after N application. There are few direct measurements of multiple gaseous emissions from N fertiliser applied to irrigated cotton farms. This study was conducted in a commercial cotton farm in NSW, Australia to measure gaseous emissions from two N fertilisation strategies (urea broadcast onto dry soil followed by irrigation, anhydrous ammonia injected into water at the main irrigation channel), with the N fertilizer rate of 27 kg N ha −1 for each application. Gas fluxes of ammonia (NH 3 ), methane (CH 4 ), and nitrous oxide (N 2 O) were measured simultaneously using an inverse-dispersion technique coupled with open-path Fourier transform infrared (OP-FTIR) spectroscopic technique, located 150 and 800 m from the input source of the irrigation water. We found that anhydrous ammonia injected into the irrigation water contributed to higher peak NH 3 emissions (0.79 ± 0.09 kg N ha −1 day −1 ) than broadcasting urea onto dry soil (-0.06 ± 0.02 kg N ha −1 day −1 ). When daily NH 3 fluxes were accumulated over 8 − 10 days, 24% of the applied N was lost as NH 3 during anhydrous ammonia application, but no N loss was detected over the course of measurement period from the broadcast urea followed by irrigation. The daily fluxes of CH 4 and N 2 O were both negative following both fertilisation events. Our study suggests that cotton farm managers should avoid the use of anhydrous NH 3 in irrigation water to mitigate the environmental impact, as well as low efficiency of N fertiliser use.

Perennial Grain Crops Reduce N &lt;sub&gt;2&lt;/sub&gt;O Emissions Under Specific Site Conditions

Perennial grain crops represent a novel hybrid between annually harvested grain crops and perennial forage crops, which are seeded once and grow for multiple subsequent seasons. Previous research has shown comparatively reduced nitrous oxide (N2O) emissions from perennial forage crops relative to annual grain crops, however, the effect of perennial grain cropping on N2O emissions is unclear. We quantified field N2O emissions along an experimental continuum of perenniality (perennial forage, perennial grain, fall grain, spring grain and fallow) established at two sites within Alberta, Canada with contrasting soils: Luvisolic at the Breton site and Chernozemic at the Edmonton site. We used static chambers and a micrometeorological technique based on an open-path Fourier-transform infrared gas sensor (OP-FTIR). Perennial grain crops reduced cumulative N2O emissions at the Breton site by 60% and 94% in years two and three of the study, respectively (Ps < 0.0001). Conversely, no reduction in N2O emissions by the perennial grain crop relative to the annual crop was evident at the Edmonton site. Correlation analyses encompassing both sites revealed that the average root density from 0-60 cm was negatively correlated with soil available nitrogen (N) (0-15 cm depth) in years one (Ps < 0.01) and two (Ps < 0.05). Moreover, in year two, root density was negatively correlated with cumulative N2O emissions, specifically at the Breton site (P < 0.01). Results suggest that the enhanced root density of perennial crops reduced soil N availability at the Breton site, which translated into reduced cumulative N2O emissions in year two. Notably, increased root density did not correlate with reduced N2O emissions at the Edmonton site, suggesting that factors such as increased soil clay and carbon content in the Chernozemic soil overrode crop controls on N2O emission. Further, OP-FTIR measurements at the Breton site were in general agreement with static chamber measurements, which collectively informed that the bulk reduction in cumulative N2O emissions occurred during spring thaw. Overall, the ability for perennial cereal grain crops to reduce N2O emissions relative to annual crops was site-specific.

Carbon exchange of a dryland cotton field and its relationship with PlanetScope remote sensing data

Agricultural systems experience numerous management-associated events during the growing season that can significantly influence seasonal and annual carbon balances. Measurements of carbon fluxes from agricultural fields using micrometeorological techniques such as eddy covariance can improve our understanding of management and weather-driven changes in carbon budgets. In-situ carbon flux data are also valuable in developing remote sensing-based models for extrapolation of biome-specific carbon budgets to higher spatial scales. In this study, net ecosystem carbon dioxide exchange (NEE) was continuously measured for two years (2017 and 2018) from a cotton (Gossypium hirsutum) field in College Station, Texas, USA. The measured NEE was partitioned into assimilatory (Gross Primary Production, GPP) and respiratory (Ecosystem respiration, Reco) fluxes. There were substantial differences in carbon fluxes between the two years, which were driven by variations in meteorological conditions and growth of weeds. Due to dry conditions, growing season carbon uptake in 2018 was reduced (883 g C m−2) compared to 2017 (947 g C m−2). While the growing season of 2018 was dry, the post-harvest off-season was remarkably wet with nearly 68% of the annual precipitation occurring after harvest (848 mm). This favored aggressive growth of weeds, resulting in substantial off-season carbon uptake in 2018 (374 g C m−2 in 2018 compared to 100 g C m−2 in 2017). Overall, the site was a net carbon source (175 g C m−2) in 2017, whereas it was a slight carbon sink (-5 g C m−2) in 2018. A significant correlation was found between satellite-derived normalized difference vegetation index (NDVI) and GPP (R2 0.78 in 2017 and 0.72 in 2018). Given that correlation, it would be possible to broaden these results to the wider region by estimating GPP with satellite data.

Short-term response of soil N-cycling genes and transcripts to fertilization with nitrification and urease inhibitors, and relationship with field-scale N2O emissions

In agroecosystems, efficient fertilizer use is key to optimizing productivity and reducing nutrient losses that can be detrimental for the environment, such as nitrous oxide (N2O) emissions. Because microbial communities regulate nitrogen (N) fate in soils, some agrochemicals inhibit specific transformations to reduce N losses. Our study aimed to describe short-term dynamics of N-cycling genes and transcripts and N2O emissions after fertilization with urea-ammonium nitrate (UAN) with or without the addition of nitrification plus urease inhibitors (NUI). The experiment consisted of 4-ha corn plots located in SE Ontario, Canada, where field-scale N2O emissions were monitored continuously using micro-meteorological techniques. Soil samples (0–10 cm) were taken 10 days before (baseline) and 2, 6, 9, 13 and 16 days after fertilization, and immediately flash-frozen. We co-extracted DNA and RNA and, using real-time PCR, quantified genes/transcripts targeting total bacteria (16S rRNA) and key N-cycling groups: ureolytic (ureC), ammonia-oxidizers (bacterial/archaeal amoA), nitrite-reducers (nirK/nirS) and N2O-reducers (clade I/II nosZ). The addition of NUI did not prevent an N2O flux event but reduced its duration and magnitude by more than 50%, and net cumulative N2O emissions for the sampling period by ~68%. NUI effects on N-cycling microorganisms were evident on day 9, as a transient reduction (40–56%) of ammonia-oxidizers and denitrifiers. Changes in transcripts were minor and only detectable on ureC (day 2), nirS and clade II nosZ (day 9). NUI did not interfere with temporal fluctuations in nirK and nirS, but it differentially affected nosZ response to a later rainfall event. Unexpectedly, N2O emissions were negatively associated with the ratio between nitrite-reducers and N2O-reducers. NUI effects on N-cycling microorganisms were minor and transient but resulted in a field-scale reduction in N2O emissions, possibly due to a combination of environmental factors and legacy effects from previous years of treatment.

Measurements and APSIM modelling of soil C and N dynamics

Process-based models capture our understanding of key processes that interact to determine productivity and environmental outcomes. Combining measurements and modelling together help assess the consequences of these interactions, identify knowledge gaps and improve understanding of these processes. Here, we present a dataset (collected in a two-month fallow period) and list potential issues related to use of the APSIM model in predicting fluxes of soil water, heat, nitrogen (N) and carbon (C). Within the APSIM framework, two soil water modules (SoilWat and SWIM3) were used to predict soil evaporation and soil moisture content. SWIM3 tended to overestimate soil evaporation immediately after rainfall events, and SoilWat provided better predictions of evaporation. Our results highlight the need for testing the modules using data that includes wetting and drying cycles. Two soil temperature modules were also evaluated. Predictions of soil temperature were better for SoilTemp than the default module. APSIM configured with different combinations of soil water and temperature modules predicted nitrate dynamics well, but poorly predicted ammonium-N dynamics. The predicted ammonium-N pool empties several weeks after fertilisation, which was not observed, indicating that the processes of mineralisation and nitrification in APSIM require improvements. The fluxes of soil respiration and nitrous oxide, measured by chamber and micrometeorological methods, were roughly captured by APSIM. Discrepancies between the fluxes measured with chamber and micrometeorological techniques highlight difficulties in obtaining accurate measurements for evaluating performance of APSIM to predict gaseous fluxes. There was uncertainty associated with soil depth, which contributed to surface emissions. Our results showed that APSIM performance in simulating N2O fluxes should be considered in relation to data precision and uncertainty, especially the soil depths included in simulations. Finally, there was a major disconnection between the predicted N loss from denitrification (N2 + N2O) and that measured using the 15N balance technique.

Decreasing ammonia loss from an Australian pasture with the use of enhanced efficiency fertilizers

Mitigating ammonia (NH3) volatilization from intensive pasture systems is critical for environmental sustainability. However, field-scale evaluation on the potential of enhanced efficiency fertilizers (e.g. urease inhibitors and controlled-release fertilizers) in mitigating NH3 volatilization is limited. Using a micrometeorological technique, we conducted two field trials to investigate the effects of Green UreaNV® (urea coated with the urease inhibitor N-(n-butyl)thiophosphoric triamide, NBPT) and polymer-coated urea (a controlled-release fertilizer) on NH3 volatilization from an intensive rainfed pasture in southern Australia. We found that NH3 volatilization from urea was 5.8 and 5.6 kg N ha–1, respectively, in the autumn and spring trials, equivalent to 11–12% of the applied urea in each season. The use of Green UreaNV® and polymer-coated urea decreased the cumulative NH3 volatilization by 45–55% and 80%, respectively. Taking into consideration the high environmental damage cost of NH3 as found in the European Union, we hypothesize that both Green UreaNV® and polymer-coated urea can be cost-effective in mitigating NH3 loss from this pasture. Our findings suggest that the extra cost of using these enhanced efficiency fertilizers for farmers is not compensated by the fertilizer N value of decreased NH3 loss. However, from a societal perspective the extra cost for Green UreaNV® is likely outweighed by reduced environmental cost of NH3. New fertilizer technology should be developed to improve the cost-effectiveness of polymer-coated urea to the farmers.

Scaling-up of evapotranspiration measurements: the promising role of scintillometry

The assessment of evapotranspiration (ET) is of primary interest, especially for agricultural and environmental issues. Traditional micrometeorological techniques require homogenous surface and are characterized by limited footprint. Thus, they cannot be applied to assess ET over inhomogeneous and extensive surfaces, typical conditions at the catchment scale and of extensive farming systems. In this context, a suitable technique to measure turbulent fluxes is scintillometry, which can give measurements of sensible heat flux at larger scale, providing averages over heterogeneous surfaces. ET can then be estimated as residual of the energy budget. In this study, we present results from a one-week campaign held during summer 2016 in Southern Italy. We deployed a Large Aperture Scintillometer (LAS) in an extensive vineyard of 140 ha on a path length of 760 m. The site was characterized by gently slope terrain with uniform crop. In order to have reference measurements of local sensible heat flux, we deployed three sonic anemometers along the scintillometer path. The aim of the study was to test the ability of scintillometry to provide a spatially averaged flux, representative of the possibly diverse conditions in an extended footprint upwind to the measurement path. The relationship between sensible heat flux measured by EC and LAS showed to be very good for the EC station in the middle of the path, whereas off-centre areas were less represented.

Measurements of Greenhouse Gas Flux from Composting Green-Waste Using Micrometeorological Mass Balance and Flow-Through Chambers

Greenhouse gases (GHGs) are produced during the composting process, but few studies have measured emissions from a full-scale windrow of composting green-waste. This is important for evaluating composting as a waste management option and for understanding how changes to current composting management practices could help reduce emissions. This study uses micrometeorological mass balance (MMB) and open flow-through chamber techniques to measure emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) from a windrow of composting green-waste in Northern California. The MMB technique yielded mean upwind–downwind concentration differences over the study period that showed sourcing of all three GHGs. CO2 showed a stronger signal than CH4 and N2O. A strong diel pattern was found in the concentration differences at lower levels and fluxes of CO2, with substantial noise likely obscuring any possible daily patterns for CH4 and N2O. Fluxes normalized by the time since the previous turn event revealed an initial rapid rise in CO2 concentration differences (at lower levels) and fluxes, peaking close to 13 h after the turn event followed by a gradual decline. The same pattern was not as clear for the other two gases but overall declines in concentration differences and fluxes were apparent with increasing time since the previous turn event. Substantial differences between MMB and chamber calculated fluxes were found, due to both differences in the techniques as well as sampling frequency.