Average Daily Flux Research Articles

Greenhouse gas emissions from temperate permanent grassland on clay-loam soil following the installation of artificial drainage

Shallow drainage (e.g. mole and gravel mole drainage installed at 0.55 m below soil surface) is used on pasture-based farms to reduce soil moisture, deepen water table depth and thus increase grass utilization on soils with impeded drainage. There is, however, a lack of research on the effect that these drainage techniques have on soil greenhouse gas (GHG) emissions. Hence the objective of this study was to investigate the effects of mole and gravel mole drainage on soil GHG fluxes. Soil nitrous oxide (N2O), soil root respiration (CO2) and soil methane (CH4) fluxes were measured in two experiments conducted over a 36 month period. The experiments were conducted on permanent grassland with impeded drainage on a eutric gleysol (humic) in Ireland (52°30′N, 08°12′W). Both experiments were arranged in randomized complete block design. There were three treatments: (i) undrained control, (ii) mole drainage and (iii) gravel mole drainage. Soil GHG fluxes, soil water filled pore space (WFPS) and soil temperature were measured on a weekly basis and soil mineral nitrogen (N), herbage N uptake, soil organic carbon (SOC) and soil total N (TN) were measured seasonally and annually over the sampling period. Drainage treatments (P < 0.05) deepened (mean ± SE) the water table by 0.17±0.03 m and decreased WFPS by 7±0.2%. However no (P > 0.05) impact of drainage treatment was detected on soil average daily GHG fluxes (9.84±6.34g N2O-N ha−1day−1, 34.05 ± 12.90 kg CO2-C ha−1day−1 and −0.91 ± 3.70 g CH4-C ha-1day-1), soil N mineralisation, soil N nitrification, SOC and TN in both experiments. The results indicate that mole and gravel mole drainage can be installed on farms with similar management and soil type to that described in the present study without impact on the soil GHG emissions.

Electron Environment Characteristics and Internal Charging Evaluation for MEO Satellite

By analyzing the newly released in situ data in medium earth orbit (MEO) of global positioning system satellites, we studied the spatiotemporal distribution and statistical characteristics of electrons over one solar cycle. The Weibull distribution of daily-averaged flux cumulative occurrence probability is proven. For >2-MeV electron flux, the determination coefficient of Weibull fitting is 99.92%. In the magnetic storm of late July 2004, the radial diffusion of electrons to low L-shell position was obvious. The center of 0.04-MeV electrons moved inward from L = 6 to L = 4.3 in the main phase and moved outward slowly in the recovery phase. In 0-4 MeV range, the in situ electron flux data are consistent with the AE9 mean and MEO-v2 model. The percentile of the AE9 model is also validated. The differential spectra are fitted based on exponential function at different percentiles. We also develop a rapid analysis method of internal charging in a changing electron environment. Using this method, we find that the electric field of internal charging fluctuates a lot because of the time-varying electron environment in MEO. The charging processes of different dielectrics (time constant ranges from 1 day to 100 days) in one solar cycle are also simulated. The longer the time constant, the bigger is the maximum charging electric field. But the worst case flux needed for discharging hazard evaluation is smaller. The daily-averaged worst case flux for charging assessment is not applicable.

Temporal shifts in controls over methane emissions from a boreal bog

We measured year-round landscape-scale methane (CH4) flux in a boreal bog from May 2014 to April 2016 using the eddy covariance technique. The objectives of the study were to investigate the controls on CH4 flux at different periods of the growing season and to quantify the annual CH4 flux budget. The daily average growing season water table (WT) ranged from -0.33 to −0.08 m in 2014 and from −0.36 to −0.08 m in 2015. Strong seasonal variability in the daily average CH4 fluxes was observed in both 2014 and 2015, ranging from near zero before May to a peak of above 20 nmol m−2 s−1 in the middle-late August in 2014 and in the early-middle September in 2015. Soil temperature at 50 cm and water table exerted interactive impact on the seasonal variation in the daily average growing season CH4 flux in both years. Soil temperature at 1 cm was negatively related to CH4 flux when water table dropped more than 0.25 m below the peat surface in 2015 growing season, suggesting that the seasonal variation in CH4 flux was dominated by the variation due to CH4 oxidation. During the non-growing season, the daily variation in CH4 fluxes was mostly related to friction velocity in both years. In addition, daily average CH4 flux was linearly related to net ecosystem exchange of CO2 (NEE) when daily NEE was negative (i.e., days with CO2 uptake larger than ecosystem respiration), but there was no correlation between them when NEE was positive (days with ecosystem respiration dominated over CO2 uptake) during the growing season. We found that this boreal bog acted as a small CH4 source of 3.7 ± 0.9 g CH4 m−2 from May 2014 to April 2015 and 3.1 ± 0.9 g CH4 m−2 from May 2015 to April 2016. These values were at the lower end of the range of CH4 emission rates reported for boreal peatlands. Non-growing season CH4 emissions accounted for 41% (the first study year) and 39% (the second study year) of the annual emissions, highlighting the importance of non-growing season CH4 emissions in estimating the annual CH4 budget and the feedback to climate.

Nitrous oxide mitigation potential of reduced tillage and N input in durum wheat in the Mediterranean

In Italy, managed soils account for about 50% of annual national emissions of nitrous oxide (N2O), thus the effect of agricultural practices on N2O emissions must be studied in order to develop mitigation strategies. Soil N2O emissions were measured in two field campaigns (2013–2014 and 2014–2015) on durum wheat in a Mediterranean environment to test the mitigation potential of reduced tillage and nitrogen (N) fertilization rate. N2O emissions were measured with a fully-transportable instrument developed during the project LIFE + IPNOA “Improved flux Prototypes for N2O emission reduction from Agriculture” and equipped with an infrared laser detector. Reducing tillage from ploughing to minimum tillage had no effect on average daily N2O flux, while decreasing the N rate from 170 to 110 kg N ha−1 reduced the average daily N2O flux, without negatively affecting the grain yield. Furthermore, N2O daily flux were positively correlated with soil water filled pore space, NO3-N, and NH4-N concentrations, and they were largely variable between the two field campaigns as a result of different environmental and management conditions (i.e.: rainfall, different amount of crop residues incorporated in soil). Overall, the innovative fully-transportable instrument performed well in the field and allowed us to conclude that decreasing the N fertilizer rate was a valuable option to mitigate N2O emissions without negative effects on wheat productivity.

Nitrous oxide (N2O) flux responds exponentially to nitrogen fertilizer in irrigated wheat in the Yaqui Valley, Mexico

The Yaqui Valley, one of Mexico’s major breadbaskets, includes ∼230,000 ha of cultivated, irrigated cropland, with two thirds of the area planted annually to spring wheat (Triticum turgidum). Nitrogen (N) fertilizer applications to wheat have doubled since the 1980s, and currently average around 300 kg N ha−1. Emissions of nitrous oxide (N2O), a potent greenhouse gas, increase following soil management activities, especially irrigation when N fertilizer is applied, and particularly when N fertilizer inputs exceed crop N requirements. Here we investigate trade–offs among N fertilizer inputs, spring wheat yields, and N2O emissions to inform management strategies that can mitigate N2O emissions without compromising yields, and link this to how farmers can generate carbon credits from N management to receive payment for more precise N use. We used static chambers to measure N2O fluxes from spring wheat at five N fertilizer rates (0, 80, 160, 240, and 280 kg N ha−1) during two growing seasons at CIMMYT in Ciudad Obregon, Sonora, Mexico. Average daily fluxes were between 1.9 ± 0.5 and 13.4 ± 2.8 g N2O-N ha−1, with lower emissions at N rates below those that maximized yield, and substantially higher emissions at N rates beyond maximum yield; this exponential response is consistent with crops in temperate regions. Results suggest that current average N fertilizer rates (300 kg N ha−1) are at least double economically optimum rates, resulting in low crop N use efficiency: 36–39% at higher N rates as compared to 50–57% for economically optimum rates. N fertilizer rate reductions to the economic optimum rates here (123 and 145 kg N ha−1 in 2013 and 2014, respectively) could have avoided N2O emissions equivalent to 0.5 to 0.8 Mg CO2e ha−1 yr−1 or, regionally, 84–138 Gg CO2e yr−1 without harming yields. Insofar as fertilizer use in Yaqui Valley is likely similar to high-productivity irrigated cereal systems elsewhere, our results provide evidence for a global triple-win scenario: large reductions in agricultural GHG emissions, increased farmer income, and continued high productivity.

Soil Carbon Dioxide Respiration in Switchgrass Fields: Assessing Annual, Seasonal and Daily Flux Patterns

Quantifications of annual soil respiration in switchgrass systems are limited to the growing season or coarse-scale temporal sampling. This study evaluates daily and seasonal soil CO2 respiration in switchgrass croplands. Hourly measurements during a 12-month period were taken for soil CO2 flux, soil temperature, and soil moisture. Although both soil temperature and moisture were positively correlated with soil CO2 flux rates, soil temperature was the primary driver of soil respiration. During winter, lower soil temperatures corresponded with significant decreases in average daily CO2 flux rates, however, CO2 pulses associated with precipitation events increased flux rates up to three times the seasonal daily average. Soil temperature influenced both daily and seasonal flux patterns where the highest flux rates, up to 31.0 kg CO2 ha−1 h−1, were observed during the warmest hours of the day (13:00 to 15:00) and during the warmest season (Summer). Summer and Spring emissions combined accounted for 80.1% of annual flux, indicating that exclusion of non-growing season time periods may result in an underestimation of total annual CO2 efflux. Our results indicate that inclusion of the non-growing season and a fine-resolution temporal sampling approach provides more accurate quantifications of total annual CO2 emissions in switchgrass croplands.

Diurnal variations and gap effects of soil CO2, N2O and CH4 fluxes in a typical tropical montane rainforest in Hainan Island, China

AbstractAccurate estimations of soil greenhouse gas (GHG) fluxes in tropical montane rainforests are critical for assessing the role of tropical forests in influencing global climate change. This research aimed to determine the diurnal variation in soil GHG fluxes and understand the effects of forest canopy gaps on GHG fluxes, and their major controlling factors. The diurnal fluxes of soil carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) inside and outside three forest canopy gaps in a tropical montane rainforest were measured with a closed static chamber system in June 2015. The main results are as follows. (1) There was an obvious single‐peak daily variation of soil GHG fluxes. (2) The averaged soil CO2, N2O and CH4 fluxes of the whole day were closest to the daily average emission fluxes at 9:00 and 12:00 for CO2, 6:00 and 9:00 for N2O, and 9:00 and 12:00 for CH4, respectively. (3) Soil CO2 and N2O emissions (positive values) and CH4 uptake (negative values) were higher inside gaps than outside. (4) There were stronger exponential relationships between soil CO2 and N2O emissions and temperature inside gaps than outside, and there was a stronger quadratic relationship between CH4 uptake and temperature outside gaps than inside. However, significant relationships between soil CO2 (or CH4) and soil moisture only occurred inside gaps (P &lt; 0.01). There were clear diurnal variations and significant effects of gaps on soil CO2, N2O and CH4 fluxes. Our study indicated that understanding the different diurnal variations of soil CO2, N2O and CH4 fluxes inside and outside canopy gaps could improve the accurate evaluation of soil GHG fluxes in tropical montane rainforests under a changing climate.

Near-zero methane emission from an abandoned boreal peatland pasture based on eddy covariance measurements.

Although estimates of the annual methane (CH4) flux from agriculturally managed peatlands exist, knowledge of controls over the variation of CH4 at different time-scales is limited due to the lack of high temporal-resolution data. Here we present CH4 fluxes measured from May 2014 to April 2016 using the eddy covariance technique at an abandoned peatland pasture in western Newfoundland, Canada. The goals of the study were to identify the controls on the seasonal variations in CH4 flux and to quantify the annual CH4 flux. The seasonal variation in daily CH4 flux was not strong in the two study years, however a few periods of pronounced emissions occurred in the late growing season. The daily average CH4 flux was small relative to other studies, ranging from -4.1 to 9.9 nmol m-2 s-1 in 2014–15 and from -7.1 to 12.1 nmol m-2 s-1 in 2015–16. Stepwise multiple regression was used to investigate controls on CH4 flux and this analysis found shifting controls on CH4 flux at different periods of the growing season. During the early growing season CH4 flux was closely related to carbon dioxide fixation rates, suggesting substrate availability was the main control. The peak growing season CH4 flux was principally controlled by the CH4 oxidation in 2014, where the CH4 flux decreased and increased with soil temperature at 50 cm and soil water content at 10 cm, but a contrasting temperature-CH4 relation was found in 2015. The late growing season CH4 flux was found to be regulated by the variation in water table level and air temperature in 2014. The annual CH4 emission was near zero in both study years (0.36 ± 0.30 g CH4 m-2 yr-1 in 2014–15 and 0.13 ± 0.38 g CH4 m-2 yr-1 in 2015–16), but fell within the range of CH4 emissions reported for agriculturally managed peatlands elsewhere.

Abundances and test weights of living planktic foraminifers across the Southwest Indian Ocean: Implications for carbon fluxes

Calcifying marine organisms include planktic foraminifers that contribute to the marine carbon turnover by generating inorganic carbon production (CaCO3, shell) and flux. In this study, we have analyzed assemblages at the morphospecies level and abundances of living planktic foraminifers (LPF) from ten stations located in the Southwest Indian Ocean, and sampled in austral summer 2012. LPF density ranges from zero in the Subtropical Zone (STZ) to 944 individuals m−3 in the Polar Frontal Zone (PFZ), and is composed by up to 80% by the four species Neogloboquadrina pachyderma, Neogloboquadrina incompta, Globigerina bulloides, and Globigerinita uvula. For the entire region, we measured the individual morphometry and test mass (CaCO3) of 454 tests of living planktic foraminifers in order to calculate inorganic carbon standing stocks, as well as carbon flux. In the STZ, the average daily planktic foraminifer CaCO3 flux at 100m water depth is low (< 0.22mgm−2 d−1), whereas south of the Sub-Antarctic Zone (SAZ), in the PFZ and Antarctic Zone (AAZ), it reaches up to 49.41mgm−2 d−1, and 2.20mgm−2 d−1, respectively. The large regional variability in CaCO3 production and flux of LPF assemblages affects the marine carbonate system to varying degrees, depending on hydrological conditions. We conclude that recent changes in the position of hydrological fronts could induce a decrease in the LPF-related carbonate counter pump, which increases the oceanic uptake of CO2, and counteracts climate warming.

Monitoring gas and heat emissions at Norris Geyser Basin, Yellowstone National Park, USA based on a combined eddy covariance and Multi-GAS approach

We quantified gas and heat emissions in an acid-sulfate, vapor-dominated area (0.04-km2) of Norris Geyser Basin, located just north of the 0.63Ma Yellowstone Caldera and near an area of anomalous uplift. From 14 May to 3 October 2016, an eddy covariance system measured half-hourly CO2, H2O and sensible (H) and latent (LE) heat fluxes and a Multi-GAS instrument measured (1Hz frequency) atmospheric H2O, CO2 and H2S volumetric mixing ratios. We also measured soil CO2 fluxes using the accumulation chamber method and temperature profiles on a grid and collected fumarole gas samples for geochemical analysis. Eddy covariance CO2 fluxes ranged from −56 to 885gm−2d−1. Using wavelet analysis, average daily eddy covariance CO2 fluxes were locally correlated with average daily environmental parameters on several-day to monthly time scales. Estimates of CO2 emission rate from the study area ranged from 8.6td−1 based on eddy covariance measurements to 9.8td−1 based on accumulation chamber measurements. Eddy covariance water vapor fluxes ranged from 1178 to 24,600gm−2d−1. Nighttime H and LE were considered representative of hydrothermal heat fluxes and ranged from 4 to 183 and 38 to 504Wm−2, respectively. The total hydrothermal heat emission rate (H+LE+radiant) estimated for the study area was 11.6MW and LE contributed 69% of the output. The mean±standard deviation of H2O, CO2 and H2S mixing ratios measured by the Multi-GAS system were 9.3±3.1 parts per thousand, 467±61ppmv, and 0.5±0.6ppmv, respectively, and variations in the gas compositions were strongly correlated with diurnal variations in environmental parameters (wind speed and direction, atmospheric temperature). After removing ambient H2O and CO2, the observed variations in the Multi-GAS data could be explained by the mixing of relatively H2O-CO2-H2S-rich fumarole gases with CO2-rich and H2O-H2S-poor soil gases. The fumarole H2O/CO2 and CO2/H2S end member ratios (101.7 and 27.1, respectively, on average) were invariant during the measurement period and fell within the range of values measured in direct fumarole gas samples. The soil gas H2O/CO2 end member ratios (~15–30) were variable and low relative to the fumarole end member, likely resulting from water vapor loss during cooling and condensation in the shallow subsurface, whereas the CO2/H2S end member ratio was high (~160), presumably related to transport of CO2-dominated soil gas emissions mixed with trace fumarolic emissions to the Multi-GAS station. Nighttime eddy covariance ratios of H2O to CO2 flux were typically between the soil gas and fumarole end member H2O/CO2 ratios defined by Multi-GAS measurements. Overall, the combined eddy covariance and Multi-GAS approach provides a powerful tool for quasi-continuous measurements of gas and heat emissions for improved volcano-hydrothermal monitoring.

A simplified sampling procedure for the estimation of methane emission in rice fields.

Manual closed chamber methods are widely used for CH4 measurement from rice paddies. Despite diurnal and seasonal variations in CH4 emissions, fixed sampling times, usually during the day, are used. Here, we monitored CH4 emission from rice paddies for one complete rice-growing season. Daytime CH4 emission increased from 0800h, and maximal emission was observed at 1200h. Daily averaged CH4 flux increased during plant growth or fertilizer application and decreased upon drainage of plants. CH4 measurement results were linearly interpolated and matched with the daily averaged CH4 emission calculated from the measured results. The time when daily averaged emission and the interpolated CH4 curve coincided during the daytime was largely invariant within each of the five distinctive periods. One-hourly sampling during each of these five periods was utilized to estimate the emission during each period, and we found that five one-hourly samples during the season accurately reflected the CH4 emission calculated based on all 136 hourly samples. This new sampling scheme is simple and more efficient than current sampling practices. Previously reported sampling schemes yielded estimates 9 to 32% higher than the measured CH4 emission, while our suggested scheme yielded an estimate that was only 5% different from that based on all 136-h samples. The sampling scheme proposed in this study can be used in rice paddy fields in Korea and extended worldwide to countries that use similar farming practices. This sampling scheme will help in producing more accurate global methane budget from rice paddy fields.

Atmospheric components of the surface energy budget over young sea ice: Results from the N‐ICE2015 campaign

AbstractThe Norwegian young sea ice campaign obtained the first measurements of the surface energy budget over young, thin Arctic sea ice through the seasonal transition from winter to summer. This campaign was the first of its kind in the North Atlantic sector of the Arctic. This study describes the atmospheric and surface conditions and the radiative and turbulent heat fluxes over young, thin sea ice. The shortwave albedo of the snow surface ranged from about 0.85 in winter to 0.72–0.80 in early summer. The near‐surface atmosphere was typically stable in winter, unstable in spring, and near neutral in summer once the surface skin temperature reached 0°C. The daily average radiative and turbulent heat fluxes typically sum to negative values (−40 to 0 W m−2) in winter but then transition toward positive values of up to nearly +60 W m−2 as solar radiation contributes significantly to the surface energy budget. The sensible heat flux typically ranges from +20–30 W m−2 in winter (into the surface) to negative values between 0 and −20 W m−2 in spring and summer. A winter case study highlights the significant effect of synoptic storms and demonstrates the complex interplay of wind, clouds, and heat and moisture advection on the surface energy components over sea ice in winter. A spring case study contrasts a rare period of 24 h of clear‐sky conditions with typical overcast conditions and highlights the impact of clouds on the surface radiation and energy budgets over young, thin sea ice.

Statistical Analysis of Extreme Electron Fluxes in the Radiation Belts

AbstractThe main aim of this work is to study the frequency of extreme Space Weather events, in particular to analyse the tails of the daily averaged electron fluxes distribution function for different channels of energy between 0.249–1.192 MeV measured at ~ 600 km of altitude with the particle detector ICARE-NG/CARMEN-1 on board argentinian polar satellite SAC-D. An extreme value theory was applied to estimate the maximum values of the electron flux in the outer radiation belt for different return levels. We found that the cumulative distribution function of the extreme electron fluxes presents a finite upper limit in (1) the core of the outer radiation belt for the lower energy channels and (2) in the inner edge of the outer radiation belt for energy channels larger than 0.653 keV. The results presented in this work are important to characterise Space Weather conditions.

Quantifying micro-environmental variation in tropical rainforest understory at landscape scale by combining airborne LiDAR scanning and a sensor network

We combined aerial LiDAR and ground sensors to map the spatial variation in micro-environmental variables of the tropical forest understory. We show that these metrics depend on forest type and proximity to canopy gaps. Our study has implications for the study of natural forest regeneration. Light impacts seedling dynamics and animals, either directly or through their effect on air temperature and relative humidity. However, the micro-environment of tropical forest understories is heterogeneous. We explored whether aerial laser scanning (LiDAR) can describe short-scale micro-environmental variables. We also studied the determinants of their spatial and intra-annual variation. We used a small-footprint LiDAR coverage combined with data obtained from 47 environmental sensors monitoring continuously understory light, moisture and temperature during 1 year over the area. We developed and tested two models relating micro-environmental conditions to LiDAR metrics. We found that a volume-based model predicts empirical light fluxes better than a model based on the proportion of the LiDAR signal reaching the ground. Understory field sensors measured an average daily light flux between 2.9 and 4.7% of full sunlight. Relative seasonal variation was comparable in the understory and in clearings. In canopy gaps, light flux was 4.3 times higher, maximal temperature 15% higher and minimal relative humidity 25% lower than in the forest understory. We found consistent micro-environmental differences among forest types. LiDAR coverage improves the fine-scale description of micro-environmental variables of tropical forest understories. This opens avenues for modelling the distribution and dynamics of animal and plant populations.

Characteristics of absorbing aerosols during winter foggy period over the National Capital Region of Delhi: Impact of planetary boundary layer dynamics and solar radiation flux

Severe air pollution in the northern India coupled with the formation of secondary pollutants results in severe fog conditions during the winter. Black carbon (BC) and particulate matter (PM2.5) play a vital role within the planetary boundary layer (PBL) to degrade atmospheric visibility. These species were continuously monitored during the winter of 2014 in the National Capital Region (NCR) of Delhi. The average BC concentration was 8.0±3.1μg/m3 with the January mean (11.1±5.4μg/m3) approximately two times higher than February (5.9±2.1μg/m3). The average PM2.5 concentration was 137±67μg/m3 with monthly area-average maximum and minima in December and February, respectively. Higher concentrations of BC at 10:00 local standard time LST (8.5μg/m3) and 22:00 LST (9.7μg/m3) were consistently observed and assigned to morning and evening rush-hour traffic across Delhi. Daily average solar fluxes, varied between 17.9 and 220.7W/m2 and had a negative correlation (r=−0.5) with BC during fog episodes. Ventilation coefficient (VC) reduced from ‘no fog’ to fog phase over Palam Airport (PLM) (0.49) times and Hindon Airport (HND) (0.28) times and from fog to prolonged fog (>14h) phase over PLM (0.35) times and HND (0.41) times, respectively, indicating high pollution over the NCR of Delhi. Ground measurements showed that daily mean aerosol optical depth at 500nm (AOD500) varied between 0.32 and 1.18 with mean AOD500 nm being highest during the prolonged fog (>14h) episodes (0.98±0.08) consistent with variations in PM2.5 and BC. Angstrom exponent (α) and Angstrom turbidity coefficient (β) were found to be >1 and 0.2, respectively, during fog showing the dominance of fine mode particles in the atmosphere.

Diversified No‐Till Crop Rotation Reduces Nitrous Oxide Emissions, Increases Soybean Yields, and Promotes Soil Carbon Accrual

Core Ideas Diversification of established no‐till, rain‐fed crop rotations was examined. Mean daily N2O fluxes were 24% lower in 4‐yr vs. 2‐yr rotation. Both no‐till rotations (2‐yr and 4‐yr) accrued soil C over this time span. 4‐yr rotation accrued soil C earlier and deeper than 2‐yr rotation. Soybean yields were 22% higher in 4‐yr vs. 2‐yr rotation. The effect of crop rotational diversity on greenhouse gas (GHG) emissions has been explored in several studies, although rarely have measurements been made on whole rotations consisting of two or more crops. We evaluated the impact of crop rotational diversity on GHG emissions, soil organic carbon (SOC), and crop yields over a 4‐yr period in eastern South Dakota, USA. Under no‐till, rain‐fed conditions, a 2‐yr (corn [Zea mays L.]–soybean [Glycine max (L.) Merr.]) rotation and a 4‐yr rotation (corn‐field peas [Pisum sativum L.]–winter wheat [Triticum aestivum L.]–soybean) were established in a randomized, complete block design (each crop present each year) 8 yr prior to the current study. Average daily N2O fluxes were 24% lower (P = 0.0313) for the 4‐yr rotation (2.34 ± 0.56 g N2O‐N ha–1d–1) compared with the 2‐yr rotation (3.06 ± 0.59 g N2O‐N ha–1d–1). Significantly elevated N2O flux peaks were observed in June of every year and every phase of the 2‐yr rotation, but only in one of 4 yr (corn phase) in the 4‐yr rotation. There was no significant difference in average daily CH4 flux between the two rotations. Over this 4‐yr period, SOC increased in the 0‐ to 15‐cm depth interval for the 2‐yr rotation, but increased in both the 0‐ to 15‐ and 15‐ to 30‐cm depth intervals for the 4‐yr rotation. Corn yields (6.75 Mg ha–1) did not differ between the two rotations. However, the yield of soybean in the 4‐yr rotation (2.87 Mg ha–1) was 22% greater (P = 0.0001) than soybean within the 2‐yr rotation (2.35 Mg ha–1). Diversified rotations can decrease N2O emissions, increase or accelerate SOC gains, distribute soil C gains deeper in the soil profile, and boost soybean yield.

Methanol emissions from maize: Ontogenetic dependence to varying light conditions and guttation as an additional factor constraining the flux

Because of its high abundance and long lifetime compared to other volatile organic compounds in the atmosphere, methanol (CH3OH) plays an important role in atmospheric chemistry. Even though agricultural crops are believed to be a large source of methanol, emission inventories from those crop ecosystems are still scarce and little information is available concerning the driving mechanisms for methanol production and emission at different developmental stages of the plants/leaves. This study focuses on methanol emissions from Zea mays L. (maize), which is vastly cultivated throughout the world. Flux measurements have been performed on young plants, almost fully grown leaves and fully grown leaves, enclosed in dynamic flow-through enclosures in a temperature and light-controlled environmental chamber. Strong differences in the response of methanol emissions to variations in PPFD (Photosynthetic Photon Flux Density) were noticed between the young plants, almost fully grown and fully grown leaves. Moreover, young maize plants showed strong emission peaks following light/dark transitions, for which guttation can be put forward as a hypothetical pathway. Young plants’ average daily methanol fluxes exceeded by a factor of 17 those of almost fully grown and fully grown leaves when expressed per leaf area. Absolute flux values were found to be smaller than those reported in the literature, but in fair agreement with recent ecosystem scale flux measurements above a maize field of the same variety as used in this study. The flux measurements in the current study were used to evaluate the dynamic biogenic volatile organic compound (BVOC) emission model of Niinemets and Reichstein. The modelled and measured fluxes from almost fully grown leaves were found to agree best when a temperature and light dependent methanol production function was applied. However, this production function turned out not to be suitable for modelling the observed emissions from the young plants, indicating that production must be influenced by (an) other parameter(s). This study clearly shows that methanol emission from maize is complex, especially for young plants. Additional studies at different developmental stages of other crop species will be required in order to develop accurate methanol emission algorithms for agricultural crops.

How many measurements are needed to estimate accurate daily and annual soil respiration fluxes? Analysis using data from a temperate rainforest

Abstract. Making accurate estimations of daily and annual Rs fluxes is key for understanding the carbon cycle process and projecting effects of climate change. In this study we used high-frequency sampling (24 measurements per day) of Rs in a temperate rainforest during 1 year, with the objective of answering the questions of when and how often measurements should be made to obtain accurate estimations of daily and annual Rs. We randomly selected data to simulate samplings of 1, 2, 4 or 6 measurements per day (distributed either during the whole day or only during daytime), combined with 4, 6, 12, 26 or 52 measurements per year. Based on the comparison of partial-data series with the full-data series, we estimated the performance of different partial sampling strategies based on bias, precision and accuracy. In the case of annual Rs estimation, we compared the performance of interpolation vs. using non-linear modelling based on soil temperature. The results show that, under our study conditions, sampling twice a day was enough to accurately estimate daily Rs (RMSE &lt; 10 % of average daily flux), even if both measurements were done during daytime. The highest reduction in RMSE for the estimation of annual Rs was achieved when increasing from four to six measurements per year, but reductions were still relevant when further increasing the frequency of sampling. We found that increasing the number of field campaigns was more effective than increasing the number of measurements per day, provided a minimum of two measurements per day was used. Including night-time measurements significantly reduced the bias and was relevant in reducing the number of field campaigns when a lower level of acceptable error (RMSE &lt; 5 %) was established. Using non-linear modelling instead of linear interpolation did improve the estimation of annual Rs, but not as expected. In conclusion, given that most of the studies of Rs use manual sampling techniques and apply only one measurement per day, we suggest performing an intensive sampling at the beginning of the study to determine minimum daily and annual frequencies of sampling.

DESIGN, CONSTRUCTION AND PERFORMANCE EVALUATION OF A SOLAR DRYING UNIT OF BASIL LEAVES

Two similar solar drying units were designed, constructed and evaluated for drying basil leaves (Ocimum basilicum L.) as a medicinal and aromatic plant at initial moisture content of 590.73% (d.b) or 85.52% (w.b) under Fayoum conditions by using heated air. Each drying unit consists of a flat-plate solar collector, which oriented and tilted with an optimum tilt angle and attached with drying chamber. The drying experiments were carried out to examine the effect of basil leaves thicknesses (2, 4 and 6 cm) and airflow rate (0.015 and 0.025 m3.sec-1) on the basil leaves drying rate. The obtained results indicated that the daily average total solar radiation flux incident on the tilted solar collector surface (29.30 MJ. m-2.day-1) was greater than that incident on the horizontal surface (24.30 MJ.m-2.day-1) by 24.58%. The output higher air temperatures were obtained at the lower airflow rate whereas; the energy gained to the air from the solar collector was relatively higher at the higher airflow rate as compared with the lower airflow rate. Consequently, the solar collector with the higher airflow rate increased the overall thermal efficiency by 5.46% as compared to the lower airflow rate. The moisture content of dried basil leaves was strongly affected by the basil leaves thickness and the airflow rate. The final moisture content of dried basil leaves ranged from (11.52% to 14.58% d.b) depending on the drying temperature cycle. Very small changes were observed in the colour and shape of heated-air dried basil leaves as compared to that dried at direct sun rays. The essential oil contents of dried basil leaves were slightly higher for the drying unit with the higher airflow rate as compared with the corresponding values obtained from the drying unit with the lower airflow at all basil leaves thicknesses. While on Contrast, total chlorophylls contents were slightly higher for the drying unit with the lower airflow rate as compared with the corresponding values obtained from the drying unit with the higher airflow at all basil leaves thicknesses. Effect of the individual variables (airflow rate, basil leaves thickness, moisture removed, and their interactions) on the drying rate was statistically analyzed. Under the conditions of this study, the optimum depth to dry basil leaves by using heated air is 4 cm.

An objective prior error quantification for regional atmospheric inverse applications

Abstract. Assigning proper prior uncertainties for inverse modelling of CO2 is of high importance, both to regularise the otherwise ill-constrained inverse problem and to quantitatively characterise the magnitude and structure of the error between prior and "true" flux. We use surface fluxes derived from three biosphere models – VPRM, ORCHIDEE, and 5PM – and compare them against daily averaged fluxes from 53 eddy covariance sites across Europe for the year 2007 and against repeated aircraft flux measurements encompassing spatial transects. In addition we create synthetic observations using modelled fluxes instead of the observed ones to explore the potential to infer prior uncertainties from model–model residuals. To ensure the realism of the synthetic data analysis, a random measurement noise was added to the modelled tower fluxes which were used as reference. The temporal autocorrelation time for tower model–data residuals was found to be around 30 days for both VPRM and ORCHIDEE but significantly different for the 5PM model with 70 days. This difference is caused by a few sites with large biases between the data and the 5PM model. The spatial correlation of the model–data residuals for all models was found to be very short, up to few tens of kilometres but with uncertainties up to 100 % of this estimation. Propagating this error structure to annual continental scale yields an uncertainty of 0.06 Gt C and strongly underestimates uncertainties typically used from atmospheric inversion systems, revealing another potential source of errors. Long spatial e-folding correlation lengths up to several hundreds of kilometres were determined when synthetic data were used. Results from repeated aircraft transects in south-western France are consistent with those obtained from the tower sites in terms of spatial autocorrelation (35 km on average) while temporal autocorrelation is markedly lower (13 days). Our findings suggest that the different prior models have a common temporal error structure. Separating the analysis of the statistics for the model data residuals by seasons did not result in any significant differences of the spatial e-folding correlation lengths.