Gas Exchange Coefficient Research Articles

CO2 fluxes at the water-atmosphere interface in fluvial environments: an overview of studies in Brazilian rivers

Recent advances in Brazilian scientific production on CO2 fluxes at the water-atmosphere interface in rivers were reviewed, including estimates of CO2 partial pressure and fluxes. A total of 17 studies were reviewed. We compiled information regarding the location studied, the methodology used by each author, and the values of CO2 partial pressure (pCO2), CO2 fluxes (FCO2), and gas exchange coefficient (k) found in each region. The results were spatialized and synthesized. The important role of fluxes in CO2 degassing and their influence on climate change, as well as the global lack of data on these environments, were the main motivations for this study. The information was scarce, and most studies are focused on the Amazon Basin. However, high-resolution mapping of CO2 fluxes, at the scale of micro basins and streams, proved to be scarce. We emphasize, therefore, the importance of further studies in the country including other hydrographic regions, and in high resolution. These studies would add to our knowledge of how natural and anthropic processes influence CO2 flux, in addition to providing better estimates in tropical river systems.
 Keywords: climate change, CO2 emission, CO2 partial pressure.

Large Uncertainties in CO2 Water–Air Outgassing Estimation with Gas Exchange Coefficient KT for a Large Lowland River

Aquatic CO2 emission is typically estimated (i.e., not measured) through a gas exchange balance. Several factors can affect the estimation, primarily flow velocity and wind speed, which can influence a key parameter, the gas exchange coefficient KT in the balancing approach. However, our knowledge of the uncertainty of predictions using these factors is rather limited. In this study, we conducted a numeric assessment on the impact of river flow velocity and wind speed on KT and the consequent CO2 emission rate. As a case study, we utilized 3-year (2019–2021) measurements on the partial pressure of dissolved carbon dioxide (pCO2) in one of the world’s largest alluvial rivers, the lower Mississippi River, to determine the difference in CO2 emission rate estimated through three approaches: velocity-based KT, wind-based KT, and a constant KT (i.e., KT = 4.3 m/day) that has been used for large rivers. Over the 3-year study period, river flow velocity varied from 0.75 ms−1 to 1.8 ms−1, and wind speed above the water surface fluctuated from 0 ms−1 to nearly 5 ms−1. Correspondingly, we obtained a velocity-based KT value of 7.80–22.11 m/day and a wind-speed-based KT of 0.77–8.40 m/day. Because of the wide variation in KT values, the estimation of CO2 emission using different approaches resulted in a substantially large difference. The velocity-based KT method yielded an average CO2 emission rate (FCO2) of 44.36 mmol m−2 h−1 for the lower Mississippi River over the 3-year study period, varying from 6.8 to 280 mmol m−2 h−1. In contrast, the wind-based KT method rendered an average FCO2 of 10.05 mmol m−2 h−1 with a small range of fluctuation (1.32–53.40 mmol m−2 h−1,), and the commonly used constant KT method produced an average FCO2 of 11.64 mmol m−2 h−1, also in a small range of fluctuation (2.42–56.87 mmol m−2 h−1). Based on the findings, we conclude that the effect of river channel geometry and flow velocity on CO2 outgassing is still largely underestimated, and the current estimation of global river CO2 emission may bear large uncertainty due to limited spatial coverage of flow conditions and the associated gas exchange variation.

Estimation of gas exchange coefficients from observations on the Yenisei River, Russia

AbstractThe gas exchange between water bodies and air is difficult to measure, thus the approximations of air–water gas exchange coefficient based solely on wind speed has been widely used. However, such approaches may not work well in river environments. In rivers, water currents may govern gas exchange. Thus, a new approximation for calculating the gas exchange coefficient (k) based on the near‐surface velocity scale (us) is suggested and compared to wind‐based estimates. Our velocity scale estimates are based on field observations during summer 2016 on the Yenisei River using an Acoustic Doppler Current Profiler, high‐frequency temperature profilers and a vessel‐mounted meteorological sensors‐suite. The results demonstrate that us‐derived gas exchange coefficients are higher than those based solely on wind speed. The results demonstrate that the wind approximation underestimates gas exchange coefficients during low‐wind conditions.

Air–water gas exchange in lakes and reservoirs measured from a moving platform by underwater eddy covariance

AbstractAir–water exchange rates of gasses, such as O2, CO2, and CH4, are widely used in ecosystem studies of lakes and reservoirs, but their magnitudes are often difficult to assess. In this proof‐of‐concept study, we measured gas exchange by underwater eddy covariance in such lentic systems from a moving platform. We used an Acoustic Doppler Velocimeter and a fast‐responding O2‐temperature sensor mounted in the bow of a boat to measure water velocity, O2 concentration, and temperature below the air–water interface (~ 10 cm) while the boat was propelled at constant speed (~ 25 cm s−1) by an electric trolling motor. Fluxes of O2 and heat across the air–water interface and standard gas exchange coefficients, k600, were calculated for every 3 min of traveled distance (~ 45 m). All deployments were done under calm low‐wind conditions where empirical relationships for k600 are most uncertain. Deployment averages of k600 ranged from 0.070 to 0.39 m d−1 and were strongly correlated with both the heat flux and the water temperature. In one deployment, a > 20% variation in mean water column O2 concentration was measured along a 1 km long transect of a reservoir. Given the typical size of O2 concentration differences over the air–water interface that drive gas exchange, such lateral variations can, even at a near‐constant exchange coefficient, result in highly biased whole‐ecosystem fluxes if based on stationary single‐point O2 measurements. “Mobile” aquatic eddy covariance measurements enable quantification of gas exchange in lakes and reservoirs under true in situ conditions and with high temporal and spatial resolution.

Physiological and metabolomics analyses of young and old leaves from wild and cultivated soybean seedlings under low-nitrogen conditions

BackgroundIt is critical to study the low nitrogen tolerance in wild soybean with extensive genetic diversity for improving cultivated soybean nitrogen use efficiency. Focusing on plant young and old leaves could provide new insights to low nitrogen tolerance research. This study compared the low nitrogen group with the control group on physiological and metabolomics changes in young and old leaves, respectively, then analyzed and compared the differences of these changes between cultivated and wild soybean. This study aimed to provide a theoretical basis for the molecular mechanism of soybean low nitrogen stress tolerance.ResultsWild soybean was less affected by low-nitrogen stress than cultivated soybean as assessed by plant biomass paraments, total carbon content and total nitrogen content. Gas-exchange coefficients and chlorophylls contents maintained relatively stable in wild soybean young leaves, but opposite in cultivated soybean. Wild soybean young leaves also increased the transport of beneficial ions, such as B3+, Fe3+, Mn2+, H2PO4− and C2O42−. In wild soybean old leaves, the nitrogen metabolism pathway was significant enhanced, especially the aspartic acid and GABA metabolisms. While in cultivated soybean, the nitrogen metabolism decreased obviously in young leaves but had no significant change in old leaves. The phenylpropanoid metabolism pathway was also activated in wild soybean. Contrary to cultivated soybeans, wild soybean tricarboxylic acid cycle and carbon metabolism including polyols and organic acids consolidated in old leaves and maintained a relative normal state in young leaves. These strategies could improve the antioxidant and N-fixation capacity in wild soybean.ConclusionThe survival and growth of wild soybean under low nitrogen stress conditions relied on physiological adjustments and metabolic changes that occurred at the cellular level. Compared with cultivated soybean, wild soybean young leaves could maintain a relatively normal growth mainly owing to a significant enhancement of key amino acids and nonprotein nitrogen metabolism in old leaves, especially aspartic acid, proline metabolism which provided basis for nitrogen reutilization from old leaves to young leaves. Consolidating the tricarboxylic acid cycle, intensifying phenylpropanoid metabolism, and accumulating more polyols and organic acids also had positive effect on it.

Headwater gas exchange quantified from O2 mass balances at the reach scale.

Headwater streams are important in the carbon cycle and there is a need to better parametrize and quantify exchange of carbon‐relevant gases. Thus, we characterized variability in the gas exchange coefficient (k 2) and dissolved oxygen (O2) gas transfer velocity (k) in two lowland headwaters of the River Avon (UK). The traditional one‐station open‐water method was complemented by in situ quantification of riverine sources and sinks of O2 (i.e., groundwater inflow, photosynthesis, and respiration in both the water column and benthic compartment) enabling direct hourly estimates of k 2 at the reach–scale (~ 150 m) without relying on the nighttime regression method. Obtained k 2 values ranged from 0.001 h−1 to 0.600 h−1. Average daytime k 2 were a factor two higher than values at night, likely due to diel changes in water temperature and wind. Temperature contributed up to 46% of the variability in k on an hourly scale, but clustering temperature incrementally strengthened the statistical relationship. Our analysis suggested that k variability is aligned with dominant temperature trends rather than with short‐term changes. Similarly, wind correlation with k increased when clustering wind speeds in increments correspondent with dominant variations (1 m s−1). Time scale is thus an important consideration when resolving physical drivers of gas exchange. Mean estimates of k 600 from recent parametrizations proposed for upscaling, when applied to the settings of this study, were found to be in agreement with our independent O2 budget assessment (within < 10%), adding further support to the validity of upscaling efforts aiming at quantifying large‐scale riverine gas emissions.

Continuous measurement of air–water gas exchange by underwater eddy covariance

Abstract. Exchange of gases, such as O2, CO2, and CH4, over the air–water interface is an important component in aquatic ecosystem studies, but exchange rates are typically measured or estimated with substantial uncertainties. This diminishes the precision of common ecosystem assessments associated with gas exchanges such as primary production, respiration, and greenhouse gas emission. Here, we used the aquatic eddy covariance technique – originally developed for benthic O2 flux measurements – right below the air–water interface (∼ 4 cm) to determine gas exchange rates and coefficients. Using an acoustic Doppler velocimeter and a fast-responding dual O2–temperature sensor mounted on a floating platform the 3-D water velocity, O2 concentration, and temperature were measured at high-speed (64 Hz). By combining these data, concurrent vertical fluxes of O2 and heat across the air–water interface were derived, and gas exchange coefficients were calculated from the former. Proof-of-concept deployments at different river sites gave standard gas exchange coefficients (k600) in the range of published values. A 40 h long deployment revealed a distinct diurnal pattern in air–water exchange of O2 that was controlled largely by physical processes (e.g., diurnal variations in air temperature and associated air–water heat fluxes) and not by biological activity (primary production and respiration). This physical control of gas exchange can be prevalent in lotic systems and adds uncertainty to assessments of biological activity that are based on measured water column O2 concentration changes. For example, in the 40 h deployment, there was near-constant river flow and insignificant winds – two main drivers of lotic gas exchange – but we found gas exchange coefficients that varied by several fold. This was presumably caused by the formation and erosion of vertical temperature–density gradients in the surface water driven by the heat flux into or out of the river that affected the turbulent mixing. This effect is unaccounted for in widely used empirical correlations for gas exchange coefficients and is another source of uncertainty in gas exchange estimates. The aquatic eddy covariance technique allows studies of air–water gas exchange processes and their controls at an unparalleled level of detail. A finding related to the new approach is that heat fluxes at the air–water interface can, contrary to those typically found in the benthic environment, be substantial and require correction of O2 sensor readings using high-speed parallel temperature measurements. Fast-responding O2 sensors are inherently sensitive to temperature changes, and if this correction is omitted, temperature fluctuations associated with the turbulent heat flux will mistakenly be recorded as O2 fluctuations and bias the O2 eddy flux calculation.

Methane dynamics downstream of a temperate run‐of‐the‐river reservoir

AbstractDams impact a significant portion of the world's rivers, and rivers downstream of the reservoirs created by large dams often emit significant amounts of methane (CH4). River CH4 emissions downstream of run‐of‐the‐river (ROR) dams are less well known. We investigated spatial and seasonal CH4 dynamics along a stretch of the Aare River (Switzerland) downstream from a bubbling ROR reservoir. We found that the CH4 horizontally accumulated in this vertically non‐stratifying ROR reservoir was consistently transported to the downstream river, but half was lost near a confluence with a tributary. We estimated CH4 diffusion using gas exchange coefficient (k) models that incorporate specific river characteristics and found CH4 emissions were threefold higher upstream of the confluence than downstream. We discuss the use of CO2‐derived k models in estimating k for CH4, and investigated it directly using a drifting chamber experiment. While chamber emissions only partly agreed with the k models, the models were robust enough to use in a CH4 mass balance along the river that indicated an overall CH4 loss from the study area. The loss predominantly occurred at the confluence and &gt; 92% of it could not be accounted for by modelled or measured CH4 emissions. Ultimately, a ROR reservoir that does not form an anoxic, CH4‐rich hypolimnion enhanced downstream river CH4 emissions, but to a lesser extent than other systems (∼9% of total reservoir‐associated emissions). Regardless, small ROR dams and river features such as confluences should be considered when measuring, estimating or upscaling river CH4 emissions.

Estimating summertime epilimnetic primary production via in situ monitoring in an eutrophic freshwater embayment, Green Bay, Lake Michigan

Abstract Quantifying rates of primary production and respiration is fundamental to understanding ecosystem function. This study utilized high-frequency time series, buoy-based sensor data to estimate daily primary production and respiration rates during the summers of 2012–2015 in southern Green Bay, Lake Michigan. Highly coherent diel oscillations of dissolved oxygen concentrations in epilimnetic waters were commonly observed for much of the summer via 30-min time intervals from the GLOS buoy (NOAA 45014) sensor array. Corrections for air–sea exchange based upon wind speed-derived gas exchange coefficients and saturation state, when combined with mixing depth, allow calculation of daytime net oxygen production and nighttime respiration. Thermistor string observations at 1-m intervals over the 13 m water depth showed the onset of thermal stratification, development of the thermocline, and occasional mixing events. For the summers of 2014 and 2015, during which a nearly continuous sensor record exists, gross primary production (GPP) and respiration (R) were estimated to be 342 ± 117 and 318 ± 83 mmol O2 m− 2 day−1 for GPP and − 325 ± 120 and − 306 ± 66 mmol O2 m− 2 day−1 for R, respectively. These results indicate that during most of the summer, southern Green Bay tends towards net autotrophy with production on average exceeding respiration by 9 ± 6% (SD). Cumulative net ecosystem production from June through September was estimated to be 3.2 and 1.3 mol C m− 2 in 2014 (118 days) and 2015 (113 days), respectively, and is sufficient to drive a significant portion of benthic respiration, the principal cause of seasonal bottom water hypoxia.

Linking aquatic metabolism, gas exchange, and hypoxia to impacts along the 300-km Grand River, Canada

The Grand River is a 7th-order 300-km river draining the largest watershed (6800 km2) in southern Ontario, Canada. The watershed has experienced large landuse changes during a period >100 y, resulting in increasing agricultural and urban nutrient inputs to the river. As a result, the Grand River is highly degraded from its source to mouth. We studied longitudinal and temporal changes in aquatic community metabolism (photosynthesis and respiration) and O2 gas exchange over 3 seasons using O2 and δ18O-O2. Diel changes in O2 saturation were >50 percentage points along the river. In some parts, the diel O2 change was >10 mg/L. Strong daily variation in δ18O-O2, up to 22‰, was observed at all 23 sampling sites in the river. Despite consistently high nutrient levels and high productivity from headwaters to mouth, wastewater treatment plant (WWTP) effluents strongly affected O2 saturation in all seasons. Modifications to river flow or nutrient inputs that affect the O2 gas-exchange coefficient or O2 demand could exacerbate current nighttime hypoxia problems. Strong diel variability in O2 may not directly indicate changes in metabolic rates because changes in gas-exchange coefficients alone are enough to mask changes in metabolic rates. Photosynthetic rates immediately downstream of WWTPs did not increase because nutrients were already high because of agricultural nutrient loading upstream of WWTPs. As a result, WWTP nutrients were exported downstream rather than used immediately below the WWTPs and the zone of impact from WWTP nutrients extended farther downstream than would otherwise be expected. O2 is the measure used by ecosystem managers, but metabolism and gas exchange must be managed to achieve the desired O2 outcomes.

Evaluation of diverse approaches for estimating sea-surface DMS concentration and air–sea exchange at global scale

Environmental context As climate models increasingly include detailed, process-based models of aerosol formation, they need to represent dimethylsulfide emissions from the ocean. Options for this include data-based climatologies and empirical or process-based models; there are diverse examples of each in the literature. This paper presents the first global-scale comparison of all available approaches and evaluation of their skill relative to observations and their possible roles in future climate models. Abstract Ocean emission and subsequent oxidation of dimethylsulfide (DMS) provides a source of sulfate in the atmosphere, potentially affecting the amount of solar radiation reaching the Earth’s surface through both direct and indirect radiative effects of sulfate aerosols. DMS concentration in the ocean is quite variable with season and location, which in turn leads to high spatial and temporal variability of ocean DMS emissions. This study tested currently available climatologies and empirical and prognostic models of DMS concentration in the surface ocean against each other and against observations. This analysis mainly reveals the limitations of estimating DMS with an empirical model based on variables such as chlorophyll and mixed-layer depth. The various empirical models show very different spatial patterns, and none correlate strongly with observations. There is considerable uncertainty in the spatial and temporal distribution of DMS concentration and flux, and in the global total DMS flux. Global total air–sea flux depends primarily on global mean surface ocean DMS concentration, and the spatial distribution of DMS concentration and the magnitude of the gas exchange coefficient are of secondary importance. Global total flux estimates range from 9 to 34TgSyear–1, with a best estimate of 18–24 Tg. Both empirical and prognostic models generally underestimate the total compared with the best available data-based estimates.

Using Green’s Functions to initialize and adjust a global, eddying ocean biogeochemistry general circulation model

The NASA Carbon Monitoring System (CMS) Flux Project aims to attribute changes in the atmospheric accumulation of carbon dioxide to spatially resolved fluxes by utilizing the full suite of NASA data, models, and assimilation capabilities. For the oceanic part of this project, we introduce ECCO2-Darwin, a new ocean biogeochemistry general circulation model based on combining the following pre-existing components: (i) a full-depth, eddying, global-ocean configuration of the Massachusetts Institute of Technology general circulation model (MITgcm), (ii) an adjoint-method-based estimate of ocean circulation from the Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) project, (iii) the MIT ecosystem model “Darwin”, and (iv) a marine carbon chemistry model. Air–sea gas exchange coefficients and initial conditions of dissolved inorganic carbon, alkalinity, and oxygen are adjusted using a Green’s Functions approach in order to optimize modeled air–sea CO2 fluxes. Data constraints include observations of carbon dioxide partial pressure (pCO2) for 2009–2010, global air–sea CO2 flux estimates, and the seasonal cycle of the Takahashi et al. (2009) Atlas. The model sensitivity experiments (or Green’s Functions) include simulations that start from different initial conditions as well as experiments that perturb air–sea gas exchange parameters and the ratio of particulate inorganic to organic carbon. The Green’s Functions approach yields a linear combination of these sensitivity experiments that minimizes model-data differences. The resulting initial conditions and gas exchange coefficients are then used to integrate the ECCO2-Darwin model forward. Despite the small number (six) of control parameters, the adjusted simulation is significantly closer to the data constraints (37% cost function reduction, i.e., reduction in the model-data difference, relative to the baseline simulation) and to independent observations (e.g., alkalinity). The adjusted air–sea gas exchange parameter differs by only 3% from the baseline value and has little impact (−0.1%) on the cost function. The particulate inorganic to organic carbon ratio was increased more than threefold and reduced the cost function by 22% relative to the baseline integration, indicating a significant influence of biology on air–sea gas exchange. The largest contribution to cost reduction (35%) comes from the adjustment of initial conditions. In addition to reducing biases relative to observations, the adjusted simulation exhibits smaller model drift than the baseline. We estimate drift by integrating the model with repeated 2009 atmospheric forcing for seven years and find a volume-weighted drift reduction of, for example, 12.5% for nitrate and 30% for oxygen in the top 300 m. Although there remain several regions with large model-data discrepancies, for example, overly strong carbon uptake in the Southern Ocean, the adjusted simulation is a first step towards a more accurate representation of the ocean carbon cycle at high spatial and temporal resolution.

Estimation of air–water gas exchange coefficient in a shallow lagoon based on 222Rn mass balance

The radon-222 mass balance is now commonly used to quantify water fluxes due to Submarine Groundwater Discharge (SGD) in coastal areas. One of the main loss terms of this mass balance, the radon evasion to the atmosphere, is based on empirical equations. This term is generally estimated using one among the many empirical equations describing the gas transfer velocity as a function of wind speed that have been proposed in the literature. These equations were, however, mainly obtained from areas of deep water and may be less appropriate for shallow areas. Here, we calculate the radon mass balance for a windy shallow coastal lagoon (mean depth of 6m and surface area of 1.55*108 m2) and use these data to estimate the radon loss to the atmosphere and the corresponding gas transfer velocity. We present new equations, adapted to our shallow water body, to express the gas transfer velocity as a function of wind speed at 10 m height (wind range from 2 to 12.5 m/s). When compared with those from the literature, these equations fit particularly well with the one of Kremer et al. (2003). Finally, we emphasize that some gas transfer exchange may always occur, even for conditions without wind.

Determination of dissolved gaseous mercury in seawater of Minamata Bay and estimation for mercury exchange across air–sea interface

Dissolved gaseous Hg (DGM) in seawater and atmospheric gaseous Hg were measured at six sites in Minamata Bay to investigate mercury (Hg) evasion flux from the sea surface. Minamata Bay was severely polluted with mono-methyl Hg (MMHg). Total Hg and MMHg, seawater characteristics such as water temperature and salinity, and meteorological parameters were also observed to estimate the air–sea exchange of Hg. The mean concentration of DGM was 116±76pgL−1 (N=75), ranging from 19 to 442pgL−1, and the concentrations were higher in summer than in other seasons. DGM concentration showed a significantly positive correlation with solar radiation, and air and water temperatures. Inversely, DGM showed a significantly negative correlation with salinity and redox potential (ORP). Hg evasion fluxes from the sea surface of the bay were calculated using a two-layer gas exchange model and ranged between 0.11 and 33ngm−2h−1 (mean, 5.4±6.3ngm−2h−1). The estimated flux was slightly higher in the spring and fall when wind speed increased because the gas exchange coefficient used for estimating Hg evasion flux strongly depends on wind speed. The annual evasion flux of Hg from the sea surface of Minamata Bay was estimated to be 47±56μgm−2, which was on the same order of magnitude as the direct atmospheric deposition flux of Hg (24μgm−2) during the observation period. Therefore, Hg evasion from the sea surface likely plays an important role in the Hg cycle of Minamata Bay.

Proper Interpretation of Dissolved Nitrous Oxide Isotopes, Production Pathways, and Emissions Requires a Modelling Approach

Stable isotopes ( 15N and 18O) of the greenhouse gas N2O provide information about the sources and processes leading to N2O production and emission from aquatic ecosystems to the atmosphere. In turn, this describes the fate of nitrogen in the aquatic environment since N2O is an obligate intermediate of denitrification and can be a by-product of nitrification. However, due to exchange with the atmosphere, the values at typical concentrations in aquatic ecosystems differ significantly from both the source of N2O and the N2O emitted to the atmosphere. A dynamic model, SIDNO, was developed to explore the relationship between the isotopic ratios of N2O, N2O source, and the emitted N2O. If the N2O production rate or isotopic ratios vary, then the N2O concentration and isotopic ratios may vary or be constant, not necessarily concomitantly, depending on the synchronicity of production rate and source isotopic ratios. Thus prima facie interpretation of patterns in dissolved N2O concentrations and isotopic ratios is difficult. The dynamic model may be used to correctly interpret diel field data and allows for the estimation of the gas exchange coefficient, N2O production rate, and the production-weighted values of the N2O source in aquatic ecosystems. Combining field data with these modelling efforts allows this critical piece of nitrogen cycling and N2O flux to the atmosphere to be assessed.

Respiratory system response to local cooling in subjects with single nucleotide polymorphism rs11562975 of the TRPM8 temperature-sensitive ion channel gene

Genome studies in ethnic Russians revealed subjects having a heterozygous genotype with allele C at the single-nucleotide polymorphism rs11562975 (G → C), which is in exon 6 of the TRPM8 temperature-sensitive ion channel gene. The subjects had increased sensitivity to cold and produced a hypometabolic response to local skin cooling and to temperature-independent activation of the TRPM8 ion channel by menthol, including a decrease in gas exchange, pulmonary ventilation, and oxygen extraction coefficient. Subjects with the homozygous genotype GG had a lower sensitivity to cold, and their response to local skin cooling was adequate in terms of thermoregulation, including a decrease in respiratory heat loss and an increase in lipid metabolism.

Inverse modeling of dissolved O2 and δ18O-DO to estimate aquatic metabolism, reaeration and respiration isotopic fractionation: effects of variable light regimes and input uncertainties

A transient model, hereafter referred to as ROM-TM, was developed to quantify river ecosystem metabolic rates and reaeration rates from field observation of changes in dissolved O2 (DO) and the ratio of 18O to 16O in DO (δ18O-DO). ROM-TM applies an inverse modeling approach and is programmed using MATLAB. Parameters describing photosynthesis, ecosystem respiration, gas exchange, and isotopic fractionation, such as maximum photosynthetic rate (Pm), photosynthetic efficiency parameter (a), respiration rate at 20 °C (R20), gas exchange coefficient (K), respiration isotopic fractionation factor (aR), and photorespiration coefficient (βR), can be abstracted by minimizing the sum of square errors between the fitted data and the observed field data. Then DO and δ18O-DO time series can be reconstructed using estimated parameters and input variables. Besides being capable of teasing apart metabolic processes and gas exchange to provide daily average estimates of metabolic parameters at the ecosystem scale, ROM-TM can be used to address issues related to light including light saturation phenomena at the ecosystem level, the effect of cloud cover on the metabolic balance, and photorespiration. Error and uncertainty analysis demonstrates that ROM-TM is stable and robust for the random errors of DO time series. The photosynthetic parameters Pm and a are more sensitive than other parameters to lower-resolution time series data.

Regional contribution of CO2 and CH4 fluxes from the fluvial network in a lowland boreal landscape of Québec

AbstractBoreal rivers and streams are known as hot spots of CO2 emissions, yet their contribution to CH4 emissions has traditionally been assumed to be negligible, due to the spatially fragmented data and lack of regional studies addressing both gases simultaneously. Here we explore the regional patterns in river CO2 and CH4 concentrations (pCO2 and pCH4), gas exchange coefficient (k), and the resulting emissions in a lowland boreal region of Northern Québec. Rivers and streams were systematically supersaturated in both gases, with both pCO2 and pCH4 declining along the river continuum. The k was on average low and increased with stream order, consistent with the hydrology of this flat landscape. The smallest streams (order 1), which represent &lt; 20% of the total river surface, contributed over 35% of the total fluvial greenhouse gas (GHG) emissions. The end of winter and the spring thaw periods, which are rarely included in annual emission budgets, contributed on average 21% of the annual GHG emissions. As a whole, the fluvial network acted as significant source of both CO2 and CH4, releasing on average 1.5 tons of C (CO2 eq) yr−1 km−2 of landscape, of which CH4 emissions contributed approximately 34%. We estimate that fluvial CH4 emissions represent 41% of the regional aquatic (lakes, reservoirs, and rivers) CH4 emissions, despite the relatively small riverine surface (4.3% of the total aquatic surface). We conclude that these fluvial networks in boreal lowlands play a disproportionately large role as hot spots for CO2 and more unexpectedly for CH4 emissions.

Modeling of CH4 combustion with NiO/NiAl2O4 in a 10 kWth CLC pilot plant

This paper presents a reactor model for combustion of CH4 with NiO/NiAl2O4 oxygen carriers in the Fuel Reactor of Chemical Looping Combustion (CLC) process. The model hydrodynamics is based on the two phase bubble - emulsion concept of bubbling fluidized beds, validated by residence time distribution tests conducted in a 10kWth equivalent cold flow prototype. The model kinetics is based on the literature and adjusted based on experimental results from a 10kWth CLC pilot plant. Results show the necessity of including both non-direct catalytic and non-catalytic direct reaction of gases on the oxygen carriers. The model shows good agreement with experimental results if some kinetic and hydrodynamic modifications are considered, including impact of gas adsorption by falling particles in the bubble phase on the gas exchange coefficient and thermodynamic limitation of CO and H2 combustion.

Development of a novel infrared technique for instantaneous, whole-field, non invasive gas concentration measurements in gas–solid fluidized beds

This work describes the development of a novel experimental technique for instantaneous whole-field, non-invasive gas concentration measurements in a gas–solid fluidized bed with high temporal and spatial resolution. The technique is based on digital image analysis of images acquired with an infrared (IR) and a visual (VIS) high-speed camera to obtain the local gas-phase carbon dioxide concentration. The IR transmission technique has first been calibrated with single gas-phase measurements using a pseudo-2D sapphire bed. Subsequently, the application of the technique has been extended to gas–solid fluidized beds by using the images on the visual wavelength range to identify and correct for the presence of the solids in the IR images. This technique allows CO2 concentration measurements in the dilute regions of the fluidized bed and in particular inside the bubbles rising bubbling gas–solid fluidized beds. The obtained concentration profiles inside a single bubble of a CO2 tracer gas injected into a fluidized bed at incipient fluidization conditions have clearly shown that the concentration inside the bubble is non-uniform while the bubble is rising up through the bed. The bubble-to-emulsion phase gas exchange coefficient computed from the measured concentration profiles deviates from literature correlations and it has been found to be dominated by convection of fluidization gas inside the bubble in the first moment and afterwards controlled by diffusion between the vortices at the right and left side of the bubble and the emulsion phase.