Monthly Air Research Articles

Historical and long-term climate trends in warm permafrost regions: A case study of Bethel, AK

Permafrost is very sensitive to climate factors, with warm permafrost particularly vulnerable to climate change. This paper aims to provide a detailed case study of climate trends of a high-latitude Alaskan site underlain by warm permafrost based on historical data and predictions from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The climate data, including air temperature, precipitation, wind speed, and their annual and seasonal trends from 1950 to 2099, are presented for Bethel, Alaska. The downscaled data are compared with the historical data in the overlap period. Both air and design freezing and thawing indices are calculated using various methods. In comparison, the downscaled model predictions align well with air temperature and wind speed records but not for precipitation, indicating the need for further downscaling at a finer resolution. The historical annual temperature records show a warming rate of 0.40 °C per decade, which is predicted to almost double to 0.78 °C per decade in the 21st century, leading to shorter winters and longer summers. The historical annual precipitation increased by a rate of 14.8 mm per decade from 1950 to 2020, and this trend is predicted to continue but at a slightly lower rate. The wind speed decreased consistently from 1984 to 2020 by 0.9 km/h per decade. However, the CMIP5 predicts that such a trend will diminish, with the mean annual wind speed remaining almost unchanged in this century. The air freezing index exhibits a consistent downtrend from 1950 to 2020, whereas the air thawing index remained flat until 1980 and rose afterward; the CMIP5 predicts that both trends will continue in the 21st century. The design air freezing and thawing indices are sensitive to the assessment periods for both methods. An assessment period shorter than 30 years, e.g., ten years, is recommended to find design indices. It is conservative to use the monthly mean air temperature method for evaluating the design air freezing index and apply the extreme event method for the design thawing index.

Electrospun Tri‐Cation Perovskite Nanofibers for Infrared Photodetection

AbstractTri‐cation (Cs+/CH3NH3+/CH(NH2)2+) and dual‐anion (Br–/I–) perovskites are promising light absorbers for inexpensive infrared (IR) photodetectors but degrade under prolonged IR exposure. Here, stable IR photodetectors based on electrospun tri‐cation perovskite fibers infiltrated with hole‐transporting π‐conjugated small molecule 2,2′,7,7′‐tetrakis[N,N‐di(4‐methoxyphenyl)amino]‐9,9‐spirobifluorene (Spiro‐OMeTAD) are demonstrated. These hybrid perovskite photodetectors operate at a low bias of 5 V and exhibit ultra‐high gains with external quantum efficiencies (EQEs) as high as 3009%, decreasing slightly to ≈2770% after 3 months in air. These EQE values are almost ten times larger than those measured for photodetectors comprising bilayer perovskite/Spiro‐OMeTAD films. A high density of charge traps on electrospun fiber surfaces gives rise to a photomultiplication effect in which photogenerated holes can travel through the active layer multiple times before recombining with trapped electrons. Time‐resolved photoluminescence and conductive atomic force microscopy mapping reveal the improved performance of electrospun fibers to originate from the significantly enhanced interfacial surface area between the perovskite and Spiro‐OMeTAD compared to bilayers. As a solution‐based, scalable and continuous method of depositing perovskite layers, electrospinning thus presents a promising strategy for the inexpensive fabrication of high‐performance IR photodetectors for applications ranging from information technology to imaging.

Assessing Gridded Precipitation and Air Temperature Products in the Ayakkum Lake, Central Asia

We evaluated the performance of gridded precipitation and air temperature datasets near the Ayakkum Lake at the southern margin of Xinjiang, arid central Asia. Statistical measures were applied to assess these climate products on a monthly basis from 2013 to 2018. For monthly precipitation amount, the European Centre for Medium-Range Weather Forecasts Reanalysis 5 shows a good performance among the five products based on most statistical measures, and the China Meteorological Forcing Dataset can also be used as an alternative, especially for estimating the long-term annual mean. For monthly air temperature, WorldClim historical weather data are recommended because of the low mean absolute error, root mean square error and distance between indices of simulation and observation. Better spatial and temporal coverages of in-situ observations are still needed to produce an optimal correction scheme for the mountainous regions of arid central Asia.

Modeling and Forecasting Selected Meteorological Parameters for the Environmental Awareness in Sub-Sahel West Africa Stations

The monthly air temperature, rainfall, air pressure, and wind speed direction for the environmental time series recorded between January 1, 1980 and December 31, 2020 in six African stations from different climatic zones were modeled and forecasted. In the forecasting, Augmented Dickey Fuller test, ARIMA models, Auto correlation Function (ACF) and Partial Autocorrelation Function (PACF) were used. Result showed that in most of the fitted models, the Moving Average terms both seasonal and non- seasonal were also significant (p<0.05) indicating that the previous day value of the stochastic term also had a significant effect on the present value of meteorological parameters in the environment. It was observed that in all the fitted models except for wind direction in Conakry and rainfall in Abidjan have all their Autoregressive term of order 1 significant (p<0.05) which implies that previous day value of these meteorological parameter had a significant effect on the present day value of the parameters. Therefore, the forecast model indicates that maximum temperature are expected in February, March, April, and June while minimum temperatures in January, August, December. Although, the selected models cannot forecast the precise air temperature, this can also provide information that can be of help to create tactics for appropriate preparation of farming which can be used as tools for effective envi­ronmental preparation and policymaking.

Temperature lapse rate estimation and snowmelt runoff simulation in a high-altitude basin

As a key parameter of hydrological process modeling, the near-surface air temperature lapse rate reflects the vertical changes in air temperature characteristics in alpine basins but often lacks the support of sufficient ground observation data. This study estimated the lapse rate of the Lhasa River Basin (LRB) from the monthly air temperature dataset (2001–2015), which was derived based on good relationships between the observed air temperature at eight gauged stations and the corresponding gridded land surface temperature of MODIS. The estimated annual average air temperature lapse rate was approximately 0.62 °C/100 m. The monthly lapse rate in different years varied seasonally in the range of 0.45–0.8 °C/100 m; the maximum was in May, and the relatively low value occurred from September to January. The snow cover in the zones with relatively low altitudes showed seasonal variation, which was consistent with the air temperature variation. Permanent snow cover appeared in the area above 5000 m and expanded with increasing elevation.

Asymmetric anionic [O⋯H⋯N]−1 -type strong H-bond constructed new near-infrared organic photothermal materials with high molar absorptivity and high amount of temperature rise

The development of photothermal materials based on perylene diimide radical anion with air-stable and near-infrared strong absorption is still challenging. We report new near-infrared perylene diimide radical anion species with high molar absorptivity and high amount of temperature rise, which was stabilized by an asymmetric anionic [O⋯H⋯N]−1-type strong H-bond between oxygen in carbonyl of perylene diimide radicals and hydrogen in amine of branched polyethyleneimine. The introduction of branched polyethyleneimine not only makes hydrogen bonding compound has good water solubility, but also inhibits the aggregation and increases the stability of radicals through steric hindrance and hydrogen bond effect. This hydrogen bonding compound shows high amount of temperature rise achieved 32.1 °C at the concentration of 0.267 mM under 808 nm laser, and it is stable enough in air for several months. An asymmetric anionic [O⋯H⋯N]−1-type strong H-bond opens a new strategy to improve the stability of perylene diimide radicals in air and the photothermal performance.

Distribution of air temperature in the territory of Ukraine against the background of current climate changes

Monitoring climatic studies of the territory helps us to establish the peculiarities of the temperature regime, to find out the indicators of the frequency and intensity of extreme weather phenomena, inherent in modern climatic conditions. The study of their trends and the variability of spatial-temporal features remain a priority area of hydrometeorological scientific and practical research. The aim of the article is to study the patterns of air temperature distribution in the territory of Ukraine for two thirty-year periods (1991-2020, 1961-1990). Main material. World and domestic research results of modern climatic conditions indicate significant warming processes observed in all seasons. Significant climatic changes for the studied territory are gaining faster pace, causing a number of problems in the socio-economic sphere, which have an impact on the country’s food security. Established trends of climatic time series of average monthly air temperature throughout the year and seasons at twenty-five meteorological stations recorded transformations of regional temperature conditions at the end of the 20th - beginning of the 21st centuries (1991-2020). Such trends in the variability of the temperature regime of the territory directly lead to further additional studies of the local and regional climate, forecasting strategies for prevention and adaptation to probable changes. The analysis of average monthly air temperature indicators during the year for the periods 1961-1990 and 1991-2020 records a warming that covers all the presented weather stations. Conclusions. The results of the study establish a steady trend towards warming of the regional climate during the period 1991-2020, drawing attention to measures of adaptability to it, further study and forecasting of climatic indicators. A feature is the rate of warming, characterized by significant growth rates, reflected in the restructuring of the regional climate and the global climate system.

Spring snow cover duration and tundra greenness in the Lena Delta, Siberia: two decades of MODIS satellite time series (2001–2021)

The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change. Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta. We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta. We extracted spring snow-cover duration determined by a latitudinal gradient. The ‘regular year’ snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta. We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed. In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021. The NDVI rise since 2018 is preceded by up to 4 °C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic.

Climatic influence on productivity of walking excavators and bulldozers in stripping in gold placer mining

The state and mineability of placer gold reserves and resources in the Russian Federation is reviewed. Judging from wide application of dragline excavators in peat cutting, it can be effective to use draglines in placer mining at depths up to 50 m due to the much lower cost of stripping compared to the other methods. In this case, it is possible to apply various schemes of direct dumping and wider employment of draglines in actual mining. It is noted that one of the highest influences on productivity of draglines and bulldozers during stripping is the presence of seasonal and perennial frost. Two groups of factors to decrease productivity of walking excavators and bulldozers at negative air temperatures are proposed. The conclusions are made about the difficulty of determining frozen ground cuttability due to the peculiarities of overburden sediment formation and because of deficient detailed studies into the properties of rocks, which govern their strength characteristics during freezing. The less labor-intensive method of calculating productivity reduction of walking excavators and bulldozers during stripping is proposed as the determination of hourly productivity reduction patterns by mathematical methods describing the random nature of phenomena, in particular, by the correlation method. The equations of the hourly productivity reduction of draglines and bulldozers depending on average monthly negative air temperature and the hourly capacity reduction factor as function of seasonal permafrost thickness and perennial permafrost cross-sections in overburden face are derived. It is noted that seasonal freezing governs reduction in productivity of excavators and bulldozers at the beginning of the warm period of the year until the permafrost is completely thawed. Stefan’s formula is suggested, according to which it is possible to calculate the depths of seasonal freezing of peat depending on the average monthly air temperature quite reliably.

Groundwater level prediction with meteorologically sensitive Gated Recurrent Unit (GRU) neural networks

Precise estimation of groundwater level (GWL) fluctuations has a substantial effect on water resources management. In the present study, to forecast the regional mean monthly time series groundwater level (GWL) with a range of 4.82 (m) in Urmia plain, three different layer structures of Gated Recurrent Unit (GRU) deep learning-based neural network models via the module of sequence-to-sequence regression are designed. In this sense, 180-time series datasets of regional mean monthly meteorological, hydrological, and observed water table depths of 42 different monitoring piezometers during the period of Oct 2002–Sep 2017 are employed as the input variables. By using Shannon entropy method, the most influential parameters on GWL are determined as regional mean monthly air temperature (Tam), precipitation (Pm), total (sum) water diversion discharge (Wdm) of four main rivers. Nevertheless, Cosine amplitude sensitivity analysis confirmed Tam as a dominant factor. For preventing overfitting problem, an algorithm tuning technique via different kinds of hyperparameters is operated. In this respect, several scenarios are implemented and the optimal hyperparameters are accomplished via the trial-and-error process. As stated by the performance evaluation metrics, Model Grading process, and Total Learnable Parameters (TLP) value, the innovative and unique suggested model (3), entitled GRU2+, (Double-GRU model coupled with Addition layer (+)) with seven layers is carefully chosen as the best model. The unique suggested model (3) in the optimal hyperparameters, resulted in an R2 of 0.91, a total grade (TG) of 7.76, an RMSE of 0.094 (m), and a running time of 47 (s). Thus, the model (3) can be certainly employed as an effective model to forecast GWL in different agricultural areas.

Persistent Radicals Derived from N-Heterocyclic Carbenes for Material Applications.

Persistent radicals are potential building blocks of novel materials in many fields. Recently, highly stable persistent radicals are considered to be within reach, thanks to several radical stabilization strategies such as spin delocalization and steric protection. N-Heterocyclic carbene (NHC)-derived substituents can be attached to a radical center for these purposes, as illustrated by numerous NHC-stabilized radicals reported in the last two decades.This Account describes our recent work on developing NHC-derived persistent radicals, as well as their prospective applications. Considering that NHCs not only stabilize radicals but also reversibly interact with gas molecules, in 2015 our group reported NHC-nitric oxide (NHC-NO) radicals produced by reversibly trapping nitric oxide (NO) radical gas in NHCs. The resultant compounds were loaded into biocompatible poly(ethylene glycol)-block-poly(caprolactone) (PEG-b-PCL) micelles and injected into tumor-bearing mice. Then, NO release was triggered by high-intensity focused ultrasound irradiation of the tumor tissue. Furthermore, the NHC-NO radicals could also serve as a platform to generate other organic radicals such as oxime ether or iminyl radicals. Apart from medicine-related applications, radicals stabilized by NHCs can be used as energy storage materials. In this context, the triazenyl radical containing two NHC units reported by our laboratory could be a cathode active material in batteries, as an organic alternative to LiCoO2. The subsequently prepared unsymmetrical triazenyl radical derivatives were applied as anolytes in nonaqueous all-organic redox flow batteries. In addition, a ferrocene-based redox flow battery anolyte was obtained by introducing NHC-derived substituents that effectively stabilize the ferrocenate derivatives previously reported only at low temperatures. The batteries containing NHC-supported radicals exhibited high energy efficiency and insignificant radical decomposition over multiple cycles. Finally, toward developing air-persistent organic radicals for flexible devices and MRI contrasting agents, we also highlight our recent air- and physiologically stable organic radicals derived from NHCs. Coordination of tris(pentafluorophenyl)borane to the NHC-NO radical produced a new radical cation that is stable in an organic solvent under air for several months. The readily accessible 1,2-dicarbonyl radical cations generated by the reaction of NHCs with oxalyl chloride are remarkably persistent even in an aqueous solution for several months. They are also highly stable even under physiological conditions, making them particularly attractive potential candidates for organic MRI contrast agents. We hope that this Account will serve as a guide for the future development of stable NHC-derived organic radicals and draw the attention of the synthetic community to their potential applications in material science.

GPRChinaTemp1km: a high-resolution monthly air temperature data set for China (1951–2020) based on machine learning

Abstract. An accurate spatially continuous air temperature data set is crucial for multiple applications in the environmental and ecological sciences. Existing spatial interpolation methods have relatively low accuracy, and the resolution of available long-term gridded products of air temperature for China is coarse. Point observations from meteorological stations can provide long-term air temperature data series but cannot represent spatially continuous information. Here, we devised a method for spatial interpolation of air temperature data from meteorological stations based on powerful machine learning tools. First, to determine the optimal method for interpolation of air temperature data, we employed three machine learning models: random forest, support vector machine, and Gaussian process regression. A comparison of the mean absolute error, root mean square error, coefficient of determination, and residuals revealed that a Gaussian process regression had high accuracy and clearly outperformed the other two models regarding the interpolation of monthly maximum, minimum, and mean air temperatures. The machine learning methods were compared with three traditional methods used frequently for spatial interpolation: inverse distance weighting, ordinary kriging, and ANUSPLIN (Australian National University Spline). Results showed that the Gaussian process regression model had higher accuracy and greater robustness than the traditional methods regarding interpolation of monthly maximum, minimum, and mean air temperatures in each month. A comparison with the TerraClimate (Monthly Climate and Climatic Water Balance for Global Terrestrial Surfaces), FLDAS (Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System), and ERA5 (ECMWF, European Centre for Medium-Range Weather Forecasts, Climate Reanalysis) data sets revealed that the accuracy of the temperature data generated using the Gaussian process regression model was higher. Finally, using the Gaussian process regression method, we produced a long-term (January 1951 to December 2020) gridded monthly air temperature data set, with 1 km resolution and high accuracy for China, which we named GPRChinaTemp1km. The data set consists of three variables: monthly mean air temperature, monthly maximum air temperature, and monthly minimum air temperature. The obtained GPRChinaTemp1km data were used to analyse the spatiotemporal variations of air temperature using Theil–Sen median trend analysis in combination with the Mann–Kendall test. It was found that the monthly mean and minimum air temperatures across China were characterised by a significant trend of increase in each month, whereas monthly maximum air temperatures showed a more spatially heterogeneous pattern, with significant increase, non-significant increase, and non-significant decrease. The GPRChinaTemp1km data set is publicly available at https://doi.org/10.5281/zenodo.5112122 (He et al., 2021a) for monthly maximum air temperature, at https://doi.org/10.5281/zenodo.5111989 (He et al., 2021b) for monthly mean air temperature, and at https://doi.org/10.5281/zenodo.5112232 (He et al., 2021c) for monthly minimum air temperature.

A terrestrial record of climate variation during MIS 11 through multiproxy palaeotemperature reconstructions from Hoxne, UK

AbstractA terrestrial (lacustrine and fluvial) palaeoclimate record from Hoxne (Suffolk, UK) shows two temperate phases separated by a cold episode, correlated with MIS 11 subdivisions corresponding to isotopic events 11.3 (Hoxnian interglacial period), 11.24 (Stratum C cold interval), and 11.23 (warm interval with evidence of human presence). A robust, reproducible multiproxy consensus approach validates and combines quantitative palaeotemperature reconstructions from three invertebrate groups (beetles, chironomids, and ostracods) and plant indicator taxa with qualitative implications of molluscs and small vertebrates. Compared with the present, interglacial mean monthly air temperatures were similar or up to 4.0°C higher in summer, but similar or as much as 3.0°C lower in winter; the Stratum C cold interval, following prolonged nondeposition or erosion of the lake bed, experienced summers 2.5°C cooler and winters between 5°C and 10°C cooler than at present. Possible reworking of fossils into Stratum C from underlying interglacial assemblages is taken into account. Oxygen and carbon isotopes from ostracod shells indicate evaporatively enriched lake water during Stratum C deposition. Comparative evaluation shows that proxy-based palaeoclimate reconstruction methods are best tested against each other and, if validated, can be used to generate more refined and robust results through multiproxy consensus.

Increased mass loss of glaciers in Volcán Domuyo (Argentinian Andes) between 1962 and 2020, revealed by aerial photos and satellite stereo imagery

AbstractWe present geodetic mass-balance estimates for ten glaciers (22.6 ± 1.1 km2) around Volcán Domuyo between 1962 and 2020 (and 46 glaciers covering 29 ± 1.5 km2 between 1984 and 2020), derived from airborne, ASTER and Pléiades imagery. Overall, we find a slightly negative mass balance (−0.15 ± 0.09 m w.e. a–1) for the entire 1962–2020 time span. A closer inspection of sub-periods reveals, however, an increasingly negative mass balance with time. The Domuyo glaciers shifted from a moderately positive mass balance of +0.28 ± 0.13 m w.e. a–1 between 1962 and 1984, to a strongly negative mass balance of −0.99 ± 0.19 m w.e. a–1 between 2012 and 2020. An increase in summer temperatures and a decrease in winter precipitation during the last four decades are likely drivers of the observed glacier changes. We support this finding by implementing a minimal glacier model, relying solely on monthly precipitation and air temperatures. The mass-balance evolution detected in Volcán Domuyo is consistent with other sites spread across the Central Andes, suggesting rapidly increasing glacier wastage impacts are occurring at a geographically wider scale.

Factorial analysis of taste quality and technological properties of cherry fruits depending on weather factors

The results of researching the fund formation of dry soluble substances, sugars, and titrated acids in cherry fruits of 10 studied varieties under the Southern Steppe Subzone of Ukraine are given. According to the content of biochemical quality indicators, the following varieties were selected: Modnytsya (the content of dry soluble substances is 17.1%), Ozhidaniye (the content of sugars is 11.7%), and Solidarnost (the content of titrated acids is 1.79%). The cherry fruits units. By conducting a two-factor dispersion analysis, the feasibility of forecasting the content of the principal components of the chemical composition (dry soluble substances, sugars, titrated acids) in the cherry fruits was determined by average values and a factor that maximally impacts the accumulation of the studied indicators was identified during the studies. The dominant influence of weather conditions during research years was determined. Therefore, the taste qualities of the cherry fruits were proposed to forecast by average varietal value. The average and strong correlation dependences of influencing 19 weather factors on the content of the studied biochemical indicators in the cherry fruits were determined. The accumulation dependence models of dry soluble substances, sugars, and titrated acids were built based on the principal component and least-squares methods. The first-rank weather indicators with the maximum influence particles were identified for the studied biochemical quality indicators. The average monthly air temperature in June maximally impacted the fund accumulation of dry soluble substances in the cherry fruits (delta = 9.9%), the content of sugars - the average monthly precipitation in June (delta = 8.5%), on the content of titrated acids - the total number of precipitation days in June (delta = 18.62%). At the end of the flowering phase before fruit ripening and in the last month of fruit formation, humidity indicators had the greatest influence on the accumulation of the studied biochemical indicators in the cherry fruits (June).of Melitopol purpura and Modnytsya have maximum indicators of the sugar-acid index in the range of 8.9-9.3 relative

A new type of cyclotron resonance from charge-impurity scattering in the bulk-insulating Bi2Se3 thin films

This work focuses on the low frequency Drude response of bulk-insulating topological insulator (TI) Bi2Se3 films. The frequency and field dependence of the mobility and carrier density are measured simultaneously via time-domain terahertz spectroscopy. These films are grown on buffer layers, capped by Se, and have been exposed in air for months. Under a magnetic field up to 7 Tesla, we observe prominent cyclotron resonances (CRs). We attribute the sharp CR to two different topological surface states from both surfaces of the films. The CR sharpens at high fields due to an electron-impurity scattering. By using magneto-terahertz spectroscopy, we confirm that these films are bulk-insulating, which paves the way to use intrinsic TIs without bulk carriers for applications including topological spintronics and quantum computing.

Seasonal And Regional Effects of Air Quality Index on Hematological Indices of Dogs Under Local Environmental Conditions In Pakistan

Air pollution is found to have significant association with living health all over global world. Environment Protection Department of Punjab, Pakistan provides the monthly air quality index (AQI) data on air pollution with concentrated particulates like PM2.5, PM10, NO2, SO2 and O3. Air particulates concentrations may vary of season, regional geography and climate. We performed blood sampling of 45 dogs from different breeds (Labrador retrievers, German shepherds and Pit bulls) from three different areas categorized on basis of AQI as less polluted (Gulberg), polluted (Town Hall) and highly polluted (Shadman) in winter and spring seasons. Data were analysed using paired sample t-tests for seasonal study and independent sample t-tests for area and breed study by SPSS (P < 0.05 ascertained as significant). Seasonal study resulted that less polluted area had no significant effects on hematological indices in any three breeds of dogs in both seasons. Polluted area was presented with increased significant effects on values of monocytes in Labrador retrievers, Hct and MCHC in German shepherds while decreased significant effects on MCH value in Pit bulls in winter season as compared to spring season. Highly polluted area had significant effects with decreasing WBC counts only in German shepherds in winter season than spring season. This study concludes that polluted and highly polluted areas in winter season with worst AQI affects blood indices more than spring season in dogs.

Experience in construction of monolithic layers of road pavement at sub-zero air temperatures

Introduction. Increasing the durability of road structures and extending the construction season for the installation of monolithic road pavements are urgent tasks. Non-rigid road pavements are of particular interest. Replacing the bases of granular materials (crushed stone, gravel, etc.) with monolithic ones reduces the material consumption of the road surface by 20-50%, the cost of construction works by up to 45% and increases the service life of roads by 1.5-2 times. The extension of the construction season for the installation of monolithic bases contributes to an increase in the pace of construction, a more rational use of road construction equipment, securing highly qualified specialists at the enterprise and reducing overhead costs. A multi-tonnage waste having independent binding properties is of particular interest, for example, belite sludge of alumina production. The article is devoted to a comprehensive study of the physical mechanical and technological properties of natural belite sludge in order to use it for the making of monolithic layers of road and airfield pavement in winter, without the introduction of antifreeze additives.Materials and methods. The freezing temperature of the belite sludge of minus 2 ° C was determined by the thermoelectric method. Its compactibility in the range of negative temperatures, the ability to restore the destroyed structure after re-compaction, the regularities of cooling of the material during technological operations for the construction of structural layers in winter are studied. The compaction was studied by pressing samples from sludge of optimal humidity, at its temperatures from 20 to minus 10°C. The study of the processes of structure formation of sludge and sludge crushed stone materials consisted in studying the kinetics of hardening of samples stored in climatic chambers that simulate changes in average monthly air temperatures in an annual cycle (from 20°C to minus 20°C) and in natural conditions (outdoors). In parallel, thermographic and electron microscopic studies of neoplasms in the hardening material were performed. To study the regularities of the cooling of the sludge layers, a laboratory experiment was conducted that simulates two-way (top and bottom) freezing of the material in a climatic chamber at temperatures of minus 10, minus 15 and minus 25°C.Results. A complex of unique physical chemical and technological properties of natural belite sludge has been identified, which consist in maintaining the initial density and activity after freezing, the ability of sludge and sludge crushed stone materials to harden at negative temperatures, a reduced freezing temperature of minus 2°C, good compaction in the range of negative temperatures (up to minus 6°C). The temperature and technological parameters of the sludge preparation for the production of works in winter are investigated. The regularities of sludge cooling in the technological process for the construction of structural layers in winter are studied. A technology has been developed for the making of monolithic layers of the road pavement made of belite sludge and crushed stone materials at negative air temperatures up to minus 20°C. The practical experience of the belite sludge use in the construction of roads in 2-4 road-climatic zones is summarized.

Geostatistical surfaces of climatological normals of mean air temperature in Minas Gerais.

Air temperature, a vital component for the terrestrial environment sustainability, can be used as an indicator and an important factor used in short- and long-term meteorological modeling at different scales. Temperature must be monitored on spatial and temporal scale with high precision. Terrain elevation can be used as the main influence factor depending on the measurement scale. In small and medium scales, factors related to local relief were modeled with geostatistics including external variables in temperature modeling. We aimed to evaluate the use of universal kriging in the modeling of air temperature in order to create temperature surfaces at each km[Formula: see text] in Minas Gerais State, Brazil using altitude, longitude and latitude covariates. The organized mean air temperature data of climatological normals of the National Institute of Meteorology were submitted to summary statistics, statistical regression and geostatistical analysis. Monthly and annual normals of the mean air temperature compensated for the period 1981 to 2010 were modeled using temperature as dependent variable and altitude, longitude and latitude as co-variables. Multiple regression modeling performed on temperature using altitude, longitude and latitude covariates determined significant parameters for monthly and annual mean air temperature global prediction. Relief and coordinates were used as external drift on variography and universal kriging with block for local temperature interpolation and prediction in order to generate 1-km moderate resolution surfaces of monthly and annual mean air temperature. Universal kriging determined smoothing effect of standard deviation of geospatial variation with prediction errors varying between 0.6 and [Formula: see text]C. Higher prediction error values were observed between June and August. Mean air temperature local prediction presented greater errors mainly in the lower altitude regions and in the colder months. In both monthly and annual temperature predictions, universal kriging with external drift enabled to circumvent the problem of performing spatial prediction from sparse punctual attribute data, conferring a temperature downscaling effect in Minas Gerais.

Modern climate warming impact on the population dynamics of the small ground squirrel (Spermophilus pygmaeus Pallas, 1778) (Rodentia, Mammalia) in the Ilmenno-Prideltovy region of the Caspian lowland

The influence of the global climate warming on the population dynamics of the small ground squirrel at the border of its range in the northern desert zone on the territory of the Ilmenno-Prideltovy landscape area of the Caspian lowland in 1945–2019 is considered. Data on the numbers of small ground squirrels and the average monthly air temperature in January–February at the Astrakhan weather stations for the last 75 years have been analyzed and statistically processed. It is emphasized that the abundance dynamics of the species is determined by a whole complex of natural and anthropogenic factors. At the same time, in desert conditions, the distribution of air temperature and precipitation by seasons and years is limiting for the small ground squirrel. The January–February temperature effect provoking the awakening of the small ground squirrel from hibernation is analyzed. The high January temperature, followed by the February cooling, led to the mass death of animals, which would subsequently negatively affect the phenology of the main phenomena in the life of this monoestral species, disrupt the population structure and lead to a decrease in the numbers of animals. Against the background of the low January air temperatures, the awakening of the small gopher took place in February–March, and the higher February temperatures provided optimal conditions for a simultaneous exit from hibernation and participation in the reproduction of all sex and age groups of small gophers. Such a combination of January and February air temperatures took place during 1960–1979, which contributed to the growth and preservation of a relatively high level of the species' abundance. The high temperatures of the 1980–2009 winter months provoked the early release of the animals from hibernation: the numbers of ground squirrels decreased and kept at a low level. Against the background of decreases temperatures of the 2010–2019 winter periods, the effect of stabilization of the small ground squirrel population and some increase in the density of the species was observed.