Water Vapor Content Research Articles

The metal-poor atmosphere of a potential sub-Neptune progenitor

Young transiting exoplanets offer a unique opportunity to characterize the atmospheres of freshly formed and evolving planets. We present the transmission spectrum of V1298 Tau b, a 23-Myr-old warm Jupiter-sized (0.91 ± 0.05 RJ, where RJ is the radius of Jupiter) planet orbiting a pre-main-sequence star. We detect a mostly clear primordial atmosphere with an exceptionally large atmospheric scale height, and a water vapour absorption at a 5σ level of significance, from which we estimate a planetary mass upper limit (23 Earth masses, 0.12 g cm−3 at a 3σ level). This is one of the lowest-density planets discovered so far. We retrieve a low atmospheric metallicity (logZ=−0.7−0.7+0.8solar\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\log{Z}=-0.{7}_{-0.7}^{+0.8}\\,{\\mathrm{solar}}$$\\end{document}), consistent with solar/sub-solar values. Our findings challenge the expected mass–metallicity relation from core-accretion theory. Our observations can instead be explained by in situ formation via pebble accretion together with ongoing evolutionary mechanisms. We do not detect methane, which hints at a hotter-than-expected interior from just the formation entropy of this planet. Our observations suggest that V1298 Tau b is likely to evolve into a sub-Neptune.

SDIPPWV: A novel hybrid prediction model based on stepwise decomposition-integration-prediction avoids future information leakage to predict precipitable water vapor from GNSS observations

Water vapor is an important meteorological parameter. Accurate prediction of water vapor content can be used to provide important reference information for heavy rainfall forecast and artificial precipitation operation. The current water vapor hybrid prediction model has the problem of future data leakage, and the error is accumulated by reconstructing the subsequence after prediction. Therefore, this paper proposes a stepwise decomposition-integration-prediction precipitable water vapor mechanism, named SDIPPWV, which can effectively solve the above problems. Firstly, High-precision precipitable water vapor (PWV) sequence is retrieved from Global Navigation Satellite System (GNSS) observation files. Then stepwise decomposition process uses a fixed-size window to segment the PWV sequence and Seasonal-Trend decomposition based on Loess (STL) to decompose the sequences within the window. Next, the features of the three sub-sequences are integrated to construct the feature space. Finally the prediction of PWV is obtained using 1D Convolutional Neural Network-Bidirectional Long Short Term Memory (1D CNN-BiLSTM). The model performance is verified using observation data from eight GNSS stations. The performance of the PWV prediction model proposed in this paper is effectively improved compared with the single prediction models and other hybrid models. The mean root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) of the eight stations are 0.2146 mm, 0.1132 mm, 1.29 %, and 0.9998, respectively. The results show that the model proposed in this paper improves the prediction accuracy of water vapor content while solving the data leakage problem.

Single-beam velocimetry with dual frequency comb absorption spectroscopy

Laser absorption Doppler velocimeters use a crossed-beam configuration to cancel errors due to laser frequency drift and absorption model uncertainty. This configuration complicates the spatial interpretation of the measurement since the two beams sample different volumes of gas. Here, we achieve single-beam velocimetry with a portable dual comb spectrometer (DCS) with high frequency accuracy and stability enabled by GPS-referencing, and a new high-temperature water vapor absorption database. We measure the inlet flow in a supersonic ramjet engine and demonstrate single-beam measurements that are on average within 19 m/s of concurrent crossed-beam measurements. We estimate that the DCS and the new database contribute 1.6 and 13 m/s to this difference respectively.

Optimization study on acid condensation and anti-corrosion performance of 3-D finned tube heat exchangers

Low-temperature acid corrosion on flue gas heat exchanger surfaces seriously reduces the stability, safety, and economy of equipment operation. Efficient strategies are urgently required to improve the anti-corrosion performance of heat exchangers. In present paper, a three-dimensional heat and mass transfer model integrating the acid dew point, acid condensation rate, and solution concentration was developed to predict the corrosion characteristics on the surfaces of 3-D finned tube heat exchangers. Firstly, a comparative analysis of acid condensate characteristics for 3-D finned tubes with different configurations was performed. The results showed that the elliptical tube effectively improves the distribution uniformity of acid condensate rate and promotes anti-corrosion performance. Then, the effects of five operating parameters (gas temperature, gas velocity, water vapor concentration, acid vapor concentration and wall temperature) on overall corrosion characteristics were systematically examined in terms of acid dew point, condensation rate and solution concentration using single-factor and orthogonal analysis, and the effect order of each factor was determined. Furthermore, optimization analysis of anti-corrosion performance was conducted based on the orthogonal results, and the optimum working conditions (water vapor concentration below 11.8% and wall temperature of 347 K to 355 K) are recommended. This research can provide theoretical guidance for the anti-corrosion designation and optimization of 3-D finned tube exchangers.

The Role of Atmospheric Stabilities and Moisture Convergence in the Enhanced Dry Season Precipitation over Land from 1979 to 2021

Abstract Between 1979 and 2021, global ocean regions experienced a decrease in dry season precipitation, while the trend over land areas varied considerably. Some regions, such as southeastern China, the Maritime Continent, eastern Europe, and eastern North America, showed a slight increasing trend in dry season precipitation. This study analyzes the potential mechanisms behind this trend by using the fifth major global reanalysis produced by ECMWF (ERA5) data. The analysis shows that the weakening of downward atmospheric motions played a critical role in enhancing dry season precipitation over land. An atmospheric moisture budget analysis revealed that larger convergent moisture fluxes lead to an increase in water vapor content below 400 hPa. This, in turn, induced an unstable tendency in the moist static energy profile, leading to a more unstable atmosphere and weakening downward motions, which drove the trend toward increasing dry season precipitation over land. More water vapor in the low troposphere is because of higher moisture convergence and moisture transport from ocean to land regions. In summary, this study demonstrates the intricate elements involved in altering dry season rainfall trends over land, which also emphasizes the importance of comprehending the spatial distribution of the wet-get-wetter and dry-get-drier paradigm. Significance Statement This study found that global land precipitation during the dry season slightly increased from 1979 to 2021, while precipitation over oceans declined. Moist static energy analysis showed a trend toward less stability in areas with increased dry season precipitation and the opposite trend in regions with declining precipitation. Water vapor content trends and dynamic components were the primary controlling mechanism for precipitation trends. Furthermore, the hotspots with pronounced increases or decreases in dry season precipitation reflect local circulation changes influenced by anthropogenic or natural factors.

The investigation of retrieval method for aerosol and water vapor profiles based on MAX-DOAS technology

Simultaneously obtaining the vertical distribution and profile of aerosol and water vapor is crucial for in-depth understanding of the Earth's radiation balance, regional water cycle, and the causes of frequent haze weather in China. This study developed a system and inversion method based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) to simultaneously retrieve tropospheric aerosol and water vapor profiles. The absorption of dioxy (O4) was obtained by multi-elevation measurement using the developed ground-based MAX-DOAS system. By minimizing a cost function combining an atmospheric radiative transfer model, aerosol extinction profiles were first inverted, followed by water vapor profiles. Optimized parameter selection in the look-up table method reduced reliance on prior profile information, enhancing pollutant distribution retrieval accuracy. In the monitoring period in Huaibei region, aerosols were mainly below 1.5 km, while water vapor concentrations decreased with altitude. Comparisons of water vapor vertical column densities (VCDs) retrieved through the look-up table method with the European Centre for Medium-Range Weather Forecasts(ECMWF) ERA5 model and geometric approximation showed good agreement, with correlation coefficients of 0.93 and 0.98, respectively. To comprehend water vapor sources at various vertical layers, a 24-h backward trajectory clustering analysis was conducted using the HYSPLIT model based on observed wind fields. Findings revealed that at 500 m altitude, water vapor primarily emanated from the southeast, whereas at 1 km and 2 km altitudes, it predominantly originated from the southwest. The study advances simultaneous tropospheric aerosol and water vapor profile retrieval, providing reliable technical support for the investigation of regional pollution.

Effect of water and ionic liquid vapors on the structural properties of gold nanoclusters formed during inert-gas condensation process using molecular dynamics simulations

In this research, process of Au nanocluster formation has been investigated using the inert-gas condensation process in different environments with different concentrations of Ar gas, water vapor, and IL molecules. We have calculated the total energy, relative stability, surface energy, and radial distribution function (RDF) of the different produced clusters at different simulation times. Our results showed that the number of formed clusters increases, whereas their size decreases by increasing the water and IL concentrations in the environment. The water and IL molecules adsorb on the nanoclusters surfaces and hinder the coalescence of the smaller clusters to form bigger clusters. The percentage of the fcc and hcp atoms also decreases by increasing the water and IL concentrations. The produced clusters also become more non-spherical by increasing the IL and water vapor in the environment (with exception of the pure vapors).

Water vapor content prediction based on neural network model selection and optimal fusion

Accurately predicting the evolution of water vapor content has significant practical engineering implications for accurately determining the timing of artificial rain enhancement operations. However, the nonlinear, unstable, and chaotic nature of water vapor content presents considerable challenges to its precise prediction. To address this, our research proposes a combined prediction model, based on a neural network model selection mechanism and small sample water vapor content data observed by microwave radiometers in the Zhengzhou area. This combined model utilizes seven neural network models as candidate models and dynamically selects the optimal three models as the central prediction components via evaluation indicators. Additionally, we employ the maximum information coefficient method to preserve the optimal input features and use a time-varying rate wave mode decomposition algorithm as the front-end processing module. This module processes the original water vapor content sequence and extracts relevant latent information. Finally, we incorporate the African vulture intelligent optimization algorithm as the backend processing component to optimize the weighted combination coefficients, achieving the integration of prediction results. Experimental results reveal that the Mean Absolute Percentage Errors (MAPE) of the proposed model on three types of water vapor content datasets are 0.208%, 0.876%, and 0.369%, respectively. This suggests a predictive performance improvement of at least 10% compared to existing models. The prediction model proposed in this study not only establishes an accurate and reliable mechanism for predicting water vapor content but also offers more comprehensive decision support information for weather modification operations.

Multiplicative effects of co-incineration of sewage sludge and wasted oyster shells in air, CO2, and steam atmospheres on P speciation and bioavailability and metal ecotoxicity

The study was aimed at the reutilization of oyster shells (OS) as a calcium-based additive to turn sewage sludge ash into phosphate fertilizer, employing the oxygen-enriched combustion technology. This process transformed all non-apatite inorganic phosphorus into apatite phosphorus with the incorporation of a 7.5% Ca-based additive. OS demonstrated comparable effectiveness to CaO in catalyzing this transformation in the oxygen-steam atmosphere. The amount of OS added and the atmosphere type significantly influenced the P bioavailability of sewage sludge ash. The oxygen-steam atmosphere, with its increased water vapor concentration, facilitated the decomposition of CaCO3 and initiated reactions with calcium phosphate to form hydroxyapatite, thus substantially enhancing P bioavailability. The oxygen-steam atmosphere increased not only metal volatilization but also the ecological toxicity of residual metals, particularly Pb, mainly in the form of F2. Excessive OS addition appeared to elevate the toxicity of Cr. Therefore, additional strategies for metal removal or passivation are needed to improve the safety of sewage sludge ash with high metal content.

Three-dimensional simulation of heat and moisture transfer in woven fabric structures

Fabric structure parameters have a significant impact on the comfort of heat and moisture transfer in garments. Previous numerical simulations required extensive mathematical calculations and mostly investigated one- or two-dimensional models of fiber assembly without considering the weave structure, which is a key parameter, that significantly influences the porosity of the woven structure and consequently its heat and moisture management. While the finite element method supports the simulation of the optimal shape and material properties with better visibility, previous finite element models focused on heat transfer and neglected water vapor transfer in fabrics. In this article, the finite element simulation of heat and moisture transfer in woven fabrics is established based on the testing principle of thermal resistance and moisture resistance tester using COMSOL Multiphysics software. In this simulation, three-dimensional parametric geometrical models of the fabric are created using curve interpolation methods by acquiring the control point coordinates of different weaves (plain, 2/2 balanced twill, and 4/1 unbalanced twill weaves). Heat and moisture transfer properties of fabric models in the horizontal and vertical directions were analyzed, including the heat flux, moisture resistance, water vapor permeability, and water vapor concentration. The article also deals with the effects of weave structure and fabric cover in a range of 72.1–85.1% on the fabric heat flux and water vapor concentration. Comparison between model and experimental results revealed that the three-dimensional simulation can accurately predict the impact of weave pattern and fabric cover on the fabric heat and moisture transfer performance. In addition, this model can be utilized to study the distribution of heat and water vapor within fabrics, providing a theoretical foundation for optimizing heat and moisture comfort in woven fabrics.

Assessment of the spectral misalignment effect (SMILE) on EarthCARE's Multi-Spectral Imager aerosol and cloud property retrievals

Abstract. The Multi-Spectral Imager (MSI) on board the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) will provide horizontal information about aerosols and clouds. These measurements are needed to extend vertical cloud and aerosol property information, which is obtained from EarthCARE's active sensors, in order to obtain a full three-dimensional view of cloud and aerosol conditions. Mesoscale weather systems, in particular, will be characterized. The discovery of a non-compliance of the MSI visible–near-infrared–shortwave infrared (VNS) camera’s visible (VIS) and shortwave infrared (SWIR1) channels regarding a spectral central wavelength (CWVL) shift across-track of up to 14 nm (VIS) and 20 nm (SWIR1) led to the need for an analysis regarding its impact on MSI Level-2A aerosol and cloud products. A significant influence of the spectral misalignment effect (SMILE) on MSI retrievals is identified due to the spectral variation in gas absorption, surface reflectance, and aerosol and cloud properties within the spectral ranges of these MSI bands. For example, the VIS channel is positioned in close proximity to the red edge of green vegetation and is impacted by residual absorption of water vapor and ozone. Small central wavelength variations introduce uncertainties due to the rapid change in surface reflectance for conditions with low optical thickness. The present central wavelength shift in the VIS towards shorter wavelengths than at nadir introduces a relative error in transmission of up to 3.3 % due to the increasing influence of water vapor and ozone absorption. We found relative errors in the top-of-atmosphere (TOA) signal due to the SMILE of up to 30 % for low optical thickness over a land surface in that band. Since the magnitude of the impact strongly depends on the underlying surface and atmospheric conditions, we conclude that accounting for the SMILE in Level-2 retrievals or correcting the Level-1 signal will improve MSI aerosol and cloud product quality.

Surface fluorinated anatase TiO2 nanosheets for NO deep oxidation in O3/H2O2 system: Enhanced mechanism and oxidation characteristics

O3 technology has exhibited promise in removing NO at low-temperature. However, challenges of high NO2 concentration that are difficult to absorb due to insufficient O3 oxidizing capacity remains. Herein, we reported an efficient strategy to generate oxygen-containing radicals for NO deep oxidation via fluorine and {001} facets modulated anatase TiO2 triggering highly activity sites that catalyzed O3/H2O2 to address the above issue. The strong electron withdrawing effect of F sites enhanced the deprotonation of H2O2, while Ti5c on {001} surface exhibited strong Lewis acid to activate O3, thermal stabilization treatment of the catalyst strengthened the synergistic effect of F and Ti5c, resulting in a 97 % NO deep oxidation efficiency at 100 °C with 3 % water vapor content. Additionally, the oxidation characteristics of the radicals was carefully discussed by occupying NO adsorption sites on TiO2 surface, the result revealed that radicals could remarkably react with gas-phase NO. Finally, the synergistic effect and oxidation properties would possess guiding significance for improving NO oxidation and applications.

Research on Landsat 8 land surface temperature retrieval and spatial–temporal migration capabilities based on random forest model

Land surface temperature (LST) plays a crucial role in characterizing land surface processes and the energy balance. Accurate monitoring of spatial–temporal variations in LST holds great significance for global and regional climate change research. However, with the increasing of multi-source remote sensing data, it has become a challenging task to construct an LST model that reduces dependence on auxiliary data (such as land surface emissivity (LSE) and atmospheric water vapor content (WVC) synchronized with satellite observations. This study proposed an LST retrieval model based on random forest model (RFLSTR). The results of 10-fold cross-validation showed that the RFLSTR model had high modelling accuracy, the root mean square error (RMSE) and mean absolute error (MAE) were lower than 2 K. Landsat 8 images from the Beijing area and South Korea, were utilized to assess the spatial–temporal migration performance of the RFLSTR model. Additionally, Landsat 9 images from South Korea were employed to analyse the sensor migration performance of the RFLSTR model. In conclusion, the findings highlight that the proposed RFLSTR model achieve high retrieval accuracy without relying on auxiliary data (such as LSE and WVC) synchronized with satellite observations. Moreover, the RFLSTR model exhibits robust spatial–temporal capabilities, enhancing the efficiency of LST retrieval and facilitating the utilization of satellite data.

Using Median Point in Keeling Plot to Reduce the Uncertainty of the Isotopic Composition of Evapotranspiration

Abstract The isotopic composition of evapotranspiration δET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculate δET, though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested the δET uncertainty using the mean point [σET (mean)] and median point [σET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. The σET (mean) would be greater than σET (median) when the mean value of inverse vapor concentration () is greater than the median value of inverse vapor concentration []. When applying the filter of r2 > 0.8, around 70% of σET (mean) was greater than σET (median). This phenomenon might be due to the normality of the vapor concentration Cυ producing the asymmetric distribution of 1/Cυ. The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentration Cυ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

Unobtrusive Sensors for Synchronous Monitoring of Different Breathing Parameters in Care Environments.

Respiratory problems are common amongst older people. The rapid increase in the ageing population has led to a need for developing technologies that can monitor such conditions unobtrusively. This paper presents a novel study that investigates Wi-Fi and ultra-wideband (UWB) antenna sensors to simultaneously monitor two different breathing parameters: respiratory rate, and exhaled breath. Experiments were carried out with two subjects undergoing three breathing cases in breaths per minute (BPM): (1) slow breathing (12 BPM), (2) moderate breathing (20 BPM), and (3) fast breathing (28 BPM). Respiratory rates were captured by Wi-Fi sensors, and the data were processed to extract the respiration rates and compared with a metronome that controlled the subjects' breathing. On the other hand, exhaled breath data were captured by a UWB antenna using a vector network analyser (VNA). Corresponding reflection coefficient data (S11) were obtained from the subjects at the time of exhalation and compared with S11 in free space. The exhaled breath data from the UWB antenna were compared with relative humidity, which was measured with a digital psychrometer during the breathing exercises to determine whether a correlation existed between the exhaled breath's water vapour content and recorded S11 data. Finally, captured respiratory rate and exhaled breath data from the antenna sensors were compared to determine whether a correlation existed between the two parameters. The results showed that the antenna sensors were capable of capturing both parameters simultaneously. However, it was found that the two parameters were uncorrelated and independent of one another.

Analysis of frost layer growth behavior on cryogenic surfaces in ultralow dew point environments by experimental tests and numerical simulations

Maintaining an ultralow dew point is essential for the operation of transonic cryogenic wind tunnels, as it significantly influences aerodynamic characteristics. Even in extremely dry conditions, minute quantities of frost can form on cryogenic surfaces, which compromises data quality. Conducting experiments on frost desublimation in such ultralow dew point environments poses significant challenges due to the demanding experimental conditions. Therefore, this study aimed to explore the desublimation characteristics of cryogenic surfaces in ultralow dew point environments and to address the challenges of experimental investigations under such extreme conditions. Initially, the study experimentally investigated frost formation by assessing the impact of various factors, such as temperature and water vapor content. It was observed that the type of frost formed depended on the water vapor content, and altering the surface temperature influenced the growth region of the frost crystals. The irregular growth of the frost layer on low-temperature surfaces was evident, as temperature markedly affected both the growth rate and the diffusion direction of frost formation. Moreover, the process of trace water frost formation was simulated using a dispersive multiphase model, predicting the frost layer's thickness. The numerical results suggest that the frost layer is micrometers thick, with a minimum thickness of 20 μm. A nonlinear relationship was identified between frost growth and dew point level. This research lays the groundwork for a deeper understanding of desublimation characteristics in ultralow dew point environments and for further investigation of low-temperature heat and mass transfer phenomena.

Physical mixing of K2CO3/Al2O3 and poly(divinylbenzene) to promote COS removal from blast furnace gas with high humidity at low temperature

Blast furnace gas (BFG) is a high emission and widely used secondary energy source. However, the presence of sulfide in BFG leads to environment pollution. Carbonyl sulfide (COS) is the main (70 %) sulfide in BFG. Catalytic hydrolysis is an important method for COS removal, but the excessive water contained in BFG can significantly inhibit the performance of hydrolysis catalyst. In present work, K2CO3 was loaded on Al2O3 support using wet impregnation method to improve its hydrolysis efficiency. Moreover, a physical mixing method was employed to combine K2CO3/Al2O3 with hydrophobic poly(divinylbenzene) (PDVB) to improve the water resistance of K2CO3/Al2O3. It was found that a simple physical mixture of PDVB with K2CO3/Al2O3 could modulate the local environment of K2CO3/Al2O3, shifting the water-sorption equilibrium on the surface of the catalyst and releasing partial water-covered catalyst surface for hydrolysis. Under the reaction temperature of 90 °C and water vapor content of 34.4 g/m3, the hydrolysis efficiency of COS increased by ∼22.5 % via mixing K2CO3/Al2O3 with PDVB. This approach demonstrates the potential to enhance the hydrolysis efficiency of catalyst for COS removal from BFG with high humidity at low temperature, which is crucial for the practical application of desulfurization of BFG.

Monitoring climate change in the marine Arctic

Changes in the temperature regime of the marine Arctic and the influencing factors are considered based on the current knowledge of the causes of climate change and the use of new data sources. In the Arctic, the warming is developing due to such factors as the increase in the transfer of heat and moisture from the low latitudes. This, in turn, drives the feedbacks in the Arctic climate system, increasing the flow of long-wave radiation to the surface due to rising atmospheric water vapor concentrations and slowing down the growth of the sea ice thickness in winter. The increase in the atmospheric heat transfer to the Arctic is associated with changes in atmospheric circulation, in particular, under the influence of ocean surface temperature anomalies, especially in the low latitudes since the bulk of the heat influx from the from solar radiation and anthropogenic forcing is accumulated here. Analyzing the causes of warming in the Arctic in the 1930s and 40s led researchers to the conclusion that the water influx from the North Atlantic is a factor to consider. Therefore, the influx of warm and salty water is also an important influence on the formation of the climate of the marine Arctic today, which should be taken into account when monitoring the temperature and ice regime of this area. Based on the analysis of the characteristics of climate variability in the marine Arctic and its causes, the article examines representative indicators of climate change in the temperature and ice regime of the marine Arctic and the factors influencing them in the present period.

Simulation of Underground Coal-Gasification Process Using Aspen Plus

In order to study the underground coal-gasification process, Aspen Plus software was used to simulate the lignite underground gasification process, and a variety of unit operation modules were selected and combined with the kinetic equations of coal underground gasification. The model can reflect the complete gasification process of the coal underground gasifier well, and the simulation results are more in line with the experimental results of the lignite underground gasification model test. The changes in the temperature and pressure of oxygen, gasification water, spray water, and syngas in pipelines were studied, and the effects of pipe diameters on pipeline conveying performance were investigated as well. The effects of the oxygen/water ratio, processing capacity, and spray-water volume on the components of syngas and components in different reaction zones were studied. In addition, the change tendency of gasification products under different conditions was researched. The results indicate that: (1) The depth of injection and the formation pressure at that depth need to be taken into account to determine a reasonable injection pressure. (2) The liquid-water injection process should select a lower injection pressure. (3) Increasing the oxygen/water ratio favors H2 production and decreasing the oxygen/water ratio favors CH4 production. (4) The content of CO2 is the highest in the oxidation zone, the lowest in the reduction zone, and then increases a little in the methanation reaction zone for the transform reaction. The content of CO is the lowest in the oxidation zone and the highest in the reduction zone. In the methanation reaction zone, CO partially converts into H2 and CO2, and the content of CO is reduced. (5) The injection of spray water does not affect the components of the gas but will increase the water vapor content in the gas; thus, this changes the molar fraction of the wet gas.

Experimental Study on Desulfurization Characteristics of Dry Sorbent Injection at Low SO2 Concentrations

AbstractTo effectively reduce SO2 emissions, flue gas desulfurization methods are widely used in coal‐fired power plants. In desulfurization, the dry sorbent injection (DSI) technology has the advantages of high desulfurization efficiency, simple operation, convenient adjustment, and low initial investment. Here, a pilot‐scale experimental system was designed and built to investigate the desulfurization characteristics of the DSI technology. The influence of the residence time of the desulfurizer, the reaction temperature, the stoichiometric ratio of the desulfurization reaction, the particle size of the desulfurizer, the inlet SO2 concentration, the dust concentration, and the water vapor content in the flue gas on the desulfurization efficiency at low SO2 concentrations was studied by injecting NaHCO3 into the pipeline. The desulfurization efficiency can be significantly improved by reducing the desulfurizer particle size or increasing the water vapor content in the flue gas at low SO2 concentration. An empirical formula describing the dependence of the desulfurization efficiency on experimental parameters is given.