scholarly journals Atmospheric Discharge Caused by Methane Emission in Permafrost Degradation Area Caused Wildfire

2021 ◽  
Author(s):  
Wei Shan ◽  
Zhichao Xu ◽  
Ying Guo ◽  
Chengcheng Zhang
Keyword(s):  
Air Temperature ◽  
Electric Potential ◽  
Methane Hydrate ◽  
Discharge Channel ◽  
Methane Concentration ◽  
Negative Charge ◽  
High Concentration ◽  
Near Surface ◽  
Methane Gas ◽  
Positively Charged

Abstract With the development of global warming, the carbon pool in the degraded permafrost zone around the Arctic will gradually be disturbed and enter the atmosphere in the form of methane gas. The frequency and intensity of forest fires will gradually increase, and the release of geological methane will become important factors affecting wildfires in permafrost regions. The northwestern section of China's Xiao Xing'an Mountains, which is located in the degradation zone of the southern edge of the permafrost region of Eurasia, was selected as the research area. Monitoring equipment such as atmospheric electric field, air temperature, methane concentration, soil temperature and pore water pressure were deployed to monitor relevant data changes for a long time. Through indoor soil ventilation tests, it was verified that the friction between gas and soil particles caused the difference in soil electric potential, and the analysis revealed the mechanism of seasonal wildfires in the study area. The results show that the gradual decomposition of metastable methane hydrate and stable methane hydrate stored in the permafrost in the northern part of the Xiao Xing'an Mountains in Northeast China is the main source of high-concentration methane gas entering the atmosphere from the surface. In spring, as the frozen layer on the surface of the study area thaws and the snow gradually melts, the high-concentration, high-pressure methane gas accumulated under the frozen layer will be quickly released into the atmosphere. The study area has the annual maximum value of methane concentration on the surface every spring (March to May), and the rapid rise of gas molecules during the decomposition of underground methane hydrate will cause friction with soil particles, causing methane molecules to be positively charged. Under the action of soil pore pressure and the negative charge at the bottom of the near-surface cloud layer, positively charged methane gas enters the atmosphere. The positively charged methane gas in the air contacts the negative charge in the near-surface cloud layer to form a discharge channel to enhance the discharge phenomenon. With the gradual accumulation of positive charges in the air, the positively charged methane in the air near the ground and the water molecules in the air form positively charged aerosols, and contact with the negative charges near the ground will also form a discharge channel to produce a discharge phenomenon, which will lead to high concentrations of methane gas near the surface were ignited. In addition, the mixed gas with higher pressure and concentration will reduce the thermal spontaneous combustion temperature of methane gas, and when methane aerosol is formed, it will further increase the impact on the air temperature, thereby increasing the risk of wildfires. The electric potential difference between the ground and the near-surface and the flammability of methane aerosols caused by the methane gas emission process in the permafrost degraded area will become an important factor in inducing wildfires.

scholarly journals Geological methane emissions and wildfire risk in the degraded permafrost area of the Xiao Xing’an Mountains, China

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wei Shan ◽  
Zhichao Xu ◽  
Ying Guo ◽  
Chengcheng Zhang ◽  
Zhaoguang Hu ◽  
...  
Keyword(s):  
Methane Hydrate ◽  
Methane Concentration ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Methane Emissions ◽  
Permafrost Region ◽  
High Concentration ◽  
Short Term ◽  
Methane Gas ◽  
Marsh Wetland

AbstractWith global warming, the carbon pool in the degradation zone of permafrost around the Arctic will gradually be disturbed and may enter the atmosphere in the form of released methane gas, becoming an important factor of environmental change in permafrost areas. We selected the northwestern section of the Xiao Xing'an Mountains in China as the study area, located in the degradation zone on the southern margin of the permafrost region in Eurasia, and set up multiple study monitoring areas equipped with methane concentration sensors, air temperature sensors, pore water pressure sensors and soil temperature sensors for long-term monitoring of data changes using the high-density electrical method, ground penetrating radar and on-site drilling to survey the distribution of frozen soil and geological conditions in the study area, combined with remote sensing images of Sentinel-2 L1C and unmanned aerial vehicle photographs and three-dimensional image reconstruction, analysis of fire activities and related geological environmental factors. The results show that since 2004, the permafrost thickness of the marsh wetland in the study area has gradually reduced and the degradation rate obviously accelerated; the organic matter and methane hydrate (metastable methane hydrate and stable methane hydrate) stored in the permafrost under the marsh wetland are gradually entering the atmosphere in the form of methane gas. Methane emissions show seasonal changes, and the annual methane emissions can be divided into three main stages, including a high-concentration short-term emission stage (March to May), a higher-concentration long-term stable emission stage (June to August) and a higher-concentration short-term emission stage (September to November); there is a certain correlation between the change in atmospheric methane concentration and the change in atmospheric pressure and pore water pressure. From March to May every year (high-concentration short-term emission stage), with snow melting, the air humidity reaches an annual low value, and the surface methane concentration reaches an annual high value. The high concentration of methane gas entering the surface in this stage is expected to increase the risk of wildfire in the permafrost degradation area in two ways (increasing the regional air temperature and self-combustion), which may be an important factor that leads to a seasonal wildfire frequency difference in the permafrost zone of Northeast China and Southeast Siberia, with the peak in spring and autumn and the monthly maximum in spring. The increase in the frequency of wildfires is projected to further generate positive feedback on climate change by affecting soil microorganisms and soil structure. Southeastern Siberia and northeastern China, which are on the southern boundary of the permafrost region of Eurasia, need to be targeted to establish fire warning and management mechanisms to effectively reduce the risk of wildfires.

Influence of nascent polypeptide positive charges on translation dynamics

2020 ◽  
Vol 477 (15) ◽  
pp. 2921-2934
Author(s):  
Rodrigo D. Requião ◽  
Géssica C. Barros ◽  
Tatiana Domitrovic ◽  
Fernando L. Palhano
Keyword(s):  
Mrna Decay ◽  
Translation Termination ◽  
Published Data ◽  
Translation Efficiency ◽  
Amino Acid Residues ◽  
High Concentration ◽  
Strong Argument ◽  
Translation Arrest ◽  
Exit Tunnel ◽  
Positively Charged

Protein segments with a high concentration of positively charged amino acid residues are often used in reporter constructs designed to activate ribosomal mRNA/protein decay pathways, such as those involving nonstop mRNA decay (NSD), no-go mRNA decay (NGD) and the ribosome quality control (RQC) complex. It has been proposed that the electrostatic interaction of the positively charged nascent peptide with the negatively charged ribosomal exit tunnel leads to translation arrest. When stalled long enough, the translation process is terminated with the degradation of the transcript and an incomplete protein. Although early experiments made a strong argument for this mechanism, other features associated with positively charged reporters, such as codon bias and mRNA and protein structure, have emerged as potent inducers of ribosome stalling. We carefully reviewed the published data on the protein and mRNA expression of artificial constructs with diverse compositions as assessed in different organisms. We concluded that, although polybasic sequences generally lead to lower translation efficiency, it appears that an aggravating factor, such as a nonoptimal codon composition, is necessary to cause translation termination events.

scholarly journals The Temperature of Halite Crystallization in the Badenian Saline Basins, in the Context of Paleoclimate Reconstruction of the Carpathian Area

Minerals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 831
Author(s):  
Anatoliy R. Galamay ◽  
Krzysztof Bukowski ◽  
Igor M. Zinczuk ◽  
Fanwei Meng
Keyword(s):  
Temperature Distribution ◽  
Air Temperature ◽  
Fluid Inclusions ◽  
Middle Miocene ◽  
Single Phase ◽  
Dead Sea ◽  
Paleoclimate Reconstruction ◽  
Near Surface ◽  
Carpathian Region ◽  
Primary Fluid

Currently, fluid inclusions in halite have been frequently studied for the purpose of paleoclimate reconstruction. For example, to determine the air temperature in the Middle Miocene (Badenian), we examine single-phase primary fluid inclusions of the bottom halites (chevron and full-faceted) and near-surface (cumulate) halites collected from the salt-bearing deposits of the Carpathian region. Our analyses showed that the temperatures of near-bottom brines varied in ranges from 19.5 to 22.0 °C and 24.0 to 26.0 °C, while the temperatures of the surface brines ranged from 34.0 to 36.0 °C. Based on these data, such as an earlier study of lithology and sedimentary structures of the Badenian rock salts, the crystallization of bottom halite developed in the basin from concentrated and cooled near-surface brines of about 30 m depth. Our results comply with the data on the temperature distribution in the modern Dead Sea.

scholarly journals Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Surface Models ◽  
Urban Heat ◽  
Soil Moisture Initialization ◽  
Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

First Principles Investigation of the Stability and the Chemical Behavior of Hydrogen in ThCoH4

2011 ◽  
Vol 66 (3) ◽  
pp. 269-274
Author(s):  
Samir F. Matar
Keyword(s):  
Negative Charge ◽  
Geometry Optimization ◽  
Full Geometry Optimization ◽  
Intermetallic Matrix ◽  
Charge Analysis ◽  
The Stability ◽  
The One ◽  
Site Selective ◽  
Bader Charge Analysis ◽  
Positively Charged

We address the changes in the electronic structure brought by the insertion of hydrogen into ThCo leading to the experimentally observed ThCoH4. Full geometry optimization positions the hydrogen in three sites stabilized in the expanded intermetallic matrix. From a Bader charge analysis, hydrogen is found to be in a narrow iono-covalent (~−0.6) to covalent (~−0.3) bonding which should enable site-selective desorption. The overall chemical picture shows a positively charged Thδ+ with the negative charge redistributed over a complex anion {CoH4}δ− with δ~1.8. Nevertheless this charge transfer remains far from the one in the more ionic hydridocobaltate anion CoH54− in Mg2CoH5, due to the largely electropositive character of Mg.

scholarly journals Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada

2021 ◽  
Author(s):  
Vidya Anderson ◽  
William A. Gough
Keyword(s):  
Urban Agriculture ◽  
Air Temperature ◽  
Green Infrastructure ◽  
Urban Climate ◽  
Surface Air Temperature ◽  
Green Roofs ◽  
Near Surface ◽  
Green Walls ◽  
The Impact ◽  
Agriculture Systems

AbstractThe application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Model Output ◽  
Intergovernmental Panel ◽  
Near Surface

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>

Phosphate biogeochemical barrier for uranium in situ immobilization in an aquifer nearby sludge repository

2021 ◽  
Author(s):  
Grigory Artemiev ◽  
Alexey Safonov ◽  
Nadezhda Popova
Keyword(s):  
Essential Elements ◽  
Ion Concentration ◽  
Soluble Form ◽  
High Concentration ◽  
Rapid Reduction ◽  
Near Surface ◽  
Nitrate Ions ◽  
Uranium Migration ◽  
Storage Facilities

<p>Uranium migration in the oxidized environment of near-surface groundwater is a typical problem of many radiochemical, ore mining and ore processing enterprises that have sludge storage facilities on their territory. Uranium migration, as a rule, occurs against a high salt background due to the composition of the sludge: primarily, nitrate and sulfate anions and calcium cations. One of the ways to prevent the uranium pollution is geochemical or engineering barriers. For uranium immobilization, it is necessary to create conditions for its reduction to a slightly soluble form of uraninite and further mineralization, for example, in the phosphate form. An important factor contributing to the rapid reduction of uranium is a in the redox potential decreasing and the removal of nitrate ions, which can be achieved through the activation of microflora. It should be added that phosphate itself is one of the essential elements for the development of microflora. This work was carried out in relation to the upper aquifer (7-12 m) near the sludge storage facilities of ChMZ, which is engaged in uranium processing and enrichment. One of the problems of this aquifer, in addition to the high concentration of nitrate ions (up to 15 g / l), is the high velocity of formation waters.<br>In laboratory conditions, the compositions of injection solutions were selected containing sources of organic matter to stimulate the microbiota development and phosphates for uranium mineralization. When developing the injection composition, special attention was paid to assessing the formation of calcite deposits in aquifer conditions to partially reduce the filtration parameters of the horizon and reduce the rate of movement of formation waters. This must be achieved to ensure the possibility of long-term deposition of uranium and removal of nitrate. The composition of the optimal solution was selected and in a series of model experiments the mineral phases containing the lowest hydrated form of the uranium-containing phosphate mineral meta-otenite were obtained.<br>In situ mineral phosphate barrier Formation field tests were carried out in water horizon conditions in a volume of 100m3 by injection of an organic and phosphates mixture. As a result, at the first stage of field work, a significant decreasing nitrate ion concentration, and reducing conditions formation coupled with the dissolved uranium concentration of decreasing were noted.</p>

scholarly journals Seasonal dynamics of methane emissions from a subarctic fen in the Hudson Bay Lowlands

2013 ◽  
Vol 10 (7) ◽  
pp. 4465-4479 ◽  
Author(s):  
K. L. Hanis ◽  
M. Tenuta ◽  
B. D. Amiro ◽  
T. N. Papakyriakou
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Growing Season ◽  
Near Surface ◽  
Growing Seasons ◽  
Air Temperatures ◽  
Soil Temperatures ◽  
Surface Soil Temperature ◽  
Filling Method ◽  
Highly Correlated

Abstract. Ecosystem-scale methane (CH4) flux (FCH4) over a subarctic fen at Churchill, Manitoba, Canada was measured to understand the magnitude of emissions during spring and fall shoulder seasons, and the growing season in relation to physical and biological conditions. FCH4 was measured using eddy covariance with a closed-path analyser in four years (2008–2011). Cumulative measured annual FCH4 (shoulder plus growing seasons) ranged from 3.0 to 9.6 g CH4 m−2 yr−1 among the four study years, with a mean of 6.5 to 7.1 g CH4 m−2 yr−1 depending upon gap-filling method. Soil temperatures to depths of 50 cm and air temperature were highly correlated with FCH4, with near-surface soil temperature at 5 cm most correlated across spring, fall, and the shoulder and growing seasons. The response of FCH4 to soil temperature at the 5 cm depth and air temperature was more than double in spring to that of fall. Emission episodes were generally not observed during spring thaw. Growing season emissions also depended upon soil and air temperatures but the water table also exerted influence, with FCH4 highest when water was 2–13 cm below and lowest when it was at or above the mean peat surface.

scholarly journals Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC<sup>4</sup>RS and DISCOVER-AQ airborne campaigns

2017 ◽  
Vol 10 (8) ◽  
pp. 3085-3104 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  
Keyword(s):  
Case Studies ◽  
Air Temperature ◽  
Initial Conditions ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Heat Fluxes ◽  
Aircraft Observation ◽  
Near Surface ◽  
Boundary Layer Height ◽  
Small Scales

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ∼ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

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