Advanced search
Accepted Online



 As the COVID-19 outbreak spread worldwide, multidisciplinary researches on COVID-19 are vastly developed, not merely focusing on the medical sciences like epidemiology and virology. One of the studies that have developed is to understand the spread of the disease. This study aims to assess the contribution of crowdsourcing-based data from social media in understanding locations and the distribution patterns of COVID-19 in Indonesia. In this study, Twitter was used as the main source to retrieve location-based active cases of COVID-19 in Indonesia. We used Netlytic ( and Phyton’s script namely GetOldTweets3 to retrieve the relevant online content about COVID-19 cases including audiences’ information such as username, time of publication, and locations from January 2020 to August 2020 when COVID-19 active cases significantly increased in Indonesia. Subsequently, the accuracy of resulted data and visualization maps was assessed by comparing the results with the official data from the Ministry of Health of Indonesia. The results show that the number of active cases and locations are only promising during the early period of the disease spread on March – April 2020, while in the subsequent periods from April to August 2020, the error was continuously exaggerated. Although the accuracy of crowdsourcing data remains a challenge, we argue that crowdsourcing platforms can be a potential data source for an early assessment of the disease spread especially for countries lacking the capital and technical knowledge to build a systematic data structure to monitor the disease spread.


The relationship between the dynamics of the atmospheric pollutants and meteorological conditions has been analyzed during the COVID-19 pandemic in Moscow in spring, 2020. The decrease in traffic emissions during the lockdown periods from March 30th until June 8th played an important role in the decrease (up to 70%) of many gaseous species and aerosol PM10 concentrations and in the increase of surface ozone (up to 18%). The analysis of the pollutant concentrations during the lockdown showed much smoother diurnal cycle for most of the species due to the reduced intensity of traffic, especially during rush hours, compared with that before and after the lockdown. The specific meteorological conditions with low temperatures during the lockdown periods as well as the observed smoke air advection have made a considerable contribution to the air quality. After removing the cases with smoke air advection the decrease in concentration of many pollutants was observed, especially in NOx  and PM10. The analysis of Pearson partial correlation coefficients with fixed temperature factor has revealed a statistically significant negative correlation between the Yandex self-isolation indices (SII), which can be used as a proxy of traffic intensity, and daily concentrations of all pollutants, except surface ozone, which has a statistically significant positive correlation with SII caused by specific photochemical reactions. In situations with SII>2.5 more favorable conditions for surface ozone generation were observed due to smaller NOx and the higher O3 /NOx ratios at the same ratio of VOC/NOx. In addition, this may also happen, since during the Arctic air advection, which was often observed during the lockdown period, the growth of ozone could be observed due to the downward flux of the ozone-rich air from the higher layers of the atmosphere.


The massive ice (MI) bodies are widespread phenomena on Chukotka coastal plains. Although they have been studying since 1930s, stable isotope method was applied for the ice beds quite recently. In this study cryostratigraphy and stable oxygen and hydrogen isotope composition of MI bodies on the extreme North-Eastern Chukotka (near Lavrentiya settlement and Koolen’ lake) have been studied in detail. It was concluded that studied MI bodies have intrasedimental origin and most likely are dated back to the Late Pleistocene age. Mean δ18O values range from –18.5 ‰ to –15 ‰ whereas mean δ2 H values range from –146‰ to –128 ‰ that is higher than expected for the Late Pleistocene ice bodies in this region, which most likely resulted from isotopic fractionation during freezing of water-saturated sediments in a closed system when forming ice became isotopically enriched compared with initial water. The analysis of co-isotope ratios for MI shows that initial water is mainly of meteoric origin (precipitation, water of lakes and taliks).


In this paper, we review both practical and theoretical assessments for evaluating radon geohazards from permafrost landforms in northern environments (>60º N). Here, we show that polar amplification (i.e. climate change) leads to the development of thawing permafrost, ground subsidence, and thawed conduits (i.e. Taliks), which allow radon migration from the subsurface to near surface environment. Based on these survey results, we conjecture that abruptly thawing permafrost soils will allow radon migration to the near surface, and likely impacting human settlements located here. We analyze potential geohazards associated with elevated ground concentrations of natural radionuclides. From these results, we apply the main existing legislation governing the control of radon parameters in the design, construction and use of buildings, as well as existing technologies for assessing the radon hazard. We found that at present, these laws do not consider our findings, namely, that increasing supply of radon to the surface during thawing of permafrost will enhance radon exposure, thereby, changing prior assumptions from which the initial legislation was determined. Hence, the legislation will likely need to respond and reconsider risk assessments of public health in relation to radon exposure. We discuss the prospects for developing radon geohazard monitoring, methodical approaches, and share recommendations based on the current state of research in permafrost effected environments. 


In this paper, the features of landscape indication of permafrost characteristics required for assessing the environmental state at various research scales are discussed. A number of permafrost characteristics affect the geoecological state and stability of natural landscapes, especially in the context of climate warming and technogenic surface disturbances. These include the distribution, temperature regime, thickness and cryogenic structure of permafrost, seasonal freezing and thawing, as well as the development of cryogenic processes. Their determination through the landscape view, however, is ambiguous. The choice of certain permafrost characteristics for geoecological assessment is based on many years of experience in creating cryo-ecological maps on a landscape basis by the school of Faculty of Geography, Moscow State University. The recent studies on the identification of regional cryoindicators are analyzed, including the issues of cryogenic landscapes classification and clarification of the boundaries of geocryological zones using the landscape structural method. The content of the two maps, «Permafrost Landscape Differentiation Map of the Russia Cryolithozone» at a scale of 1: 15,000,000 and «Permafrost Landscape Map of the Republic of Sakha (Yakutia)» at a scale of 1: 1,500,000, is presented, as well as their use as a basis for environmental planning and geoecological assessment.



We analyzed four years field observations (2017–2020) of soil CO2 efflux from Chernozems of arable and foreststeppe ecosystems of Kursk region (Russia), which correspond to the period of the maximal current warming. Three wellknown simulation models of different structure and variable sets (DNDC, RothC, T&P) and nonparametric regression analysis were used to estimate annual CO2 emission from soil and contributions of constant and sporadic controls. The applied models satisfactorily predict both the rate of annual soil CO2 emission and its seasonal dynamics on arable Chernozems. However, while RothC is suitable for the whole set of crops considered, DNDC is most suitable for cereals and T&R for bare soils only. A comparison of the contributions of permanent and sporadic factors to soil respiration showed that on an inter-annual scale soil temperature and moisture are less important than yearly crop rotation in Chernozem plowlands, making the latter the most important predictor apart from general land-use type. Although the combination of significant permanent and sporadic factors is able to explain 41% of the soil CO2 emission variance, the leading involvement of spatial controls prevents the construction of quantitative regression models that are able to make forecasts, requiring the use of more sophisticated simulation models (i.e. RothC) in this case. However, the use of the latter does not yet solve the problem of predicting soil CO2 emission and its net balance in forest-covered or steppe areas of Chernozem forest-steppe landscape.


The COVID-19 pandemic has had a major impact on various sectors. Iran is one of the countries most affected by this pandemic. After considering the huge impact, the government imposed strict rules prohibiting social gatherings and restricting travel for the entire population following the large number of victims in the country. These restrictions lead to changes in the environment, especially air quality. The purpose of this study was to find out how the COVID-19 pandemic affected air quality in Iran following the activity restrictions in the region. The method used in this research was based on the use of multitemporal Sentinel-5P data processing with scripts available on the Google Earth Engine applied on the images, acquired in the period before and after the COVID-19 pandemic. The data used included the image collection of Sentinel-5P NRTI CO: Near Real-Time Carbon Monoxide, Sentinel-5P NRTI NO2: Near Real-Time Nitrogen Dioxide and Sentinel-5P NRTI SO2: Near Real-Time Sulphur Dioxide. The results showed, that for Iran in general, changes in the concentration of CO are clearly visible in urban areas with high population activity such as Tehran, where there was a decrease from 0.05 to 0.0286 mol/m2, while for other areas it is also influenced by the varying climate conditions, which affect the level of pollution. For the NO2 pollutant, there was a significant decrease in pollution levels in big cities such as Tehran, Qom, Isfahan and Mashhad from 0.0002 to 0.000114 mol/m2. For the SO2 pollutant, there was a decrease in pollution levels in Iran’s big cities from 0.0005 to 0.0000714 mol/m2. For Tehran province, which is the most populous and busiest province in Iran, it can be observed that there was also a decrease in the concentration of pollutants after the lockdown compared to the pre-lockdown period. The CO concentration decreased from 0.043 to 0.036 mol/m2, while for the NO2 pollutant there was a decrease from 0.0002 to 0.000142 mol/m2 and for the SO2 pollutant, there was a decrease from 0.0005 to 0.000143 mol/m2.


In the paper, we consider a method of ground temperature monitoring using the thermometric boreholes and computer modeling the residential buildings with the pile foundation in the city of Salekhard; note that it is located in the permafrost zone. Construction of the residential buildings and industrial structures in the permafrost zone and their operation is carried out according to the principle of preserving the frozen state of foundations. For ground temperature monitoring, thermometric boreholes are used. In a given time period, the measured temperatures are transferred to a server for further processing. Information about the temperature is an important factor for the safety of the buildings and it can be used to evaluate the piles bearing capacity. It allows to propose options for the soil thermal stabilization or to eliminate the detected technogenic heat sources. An approach of mathematical modeling to reconstruct the temperature fields in the pile foundation base of a building is discussed taking into account the data of temperature monitoring. 24 boreholes were equipped with more than 400 in-borehole thermal sensors for testing the method under the residential building I. The preliminary modeling is carried out for December and January 2020 for the contact thermal conductivity model with phase transition with the upper part of the geological section typical for Salekhard (the sandy soils). The modeling describes the freezing processes during the months in detail. The thermal monitoring allows to say that the ground in the base of the Residential building I is stable. But there are detected heat transfers near the borehole T1 at the depth of 12–14 m. The combination of monitoring and computer modeling makes it possible to assess the safety of the operation of the residential buildings in cities located in the permafrost zones.



The Infrastructure stability on permafrost is currently an important topic as the Arctic countries are developing climate change adaptation and mitigation programs. Assessing the sustainability of infrastructure facilities (especially in urban environments) is a difficult task as it depends on many parameters. This article discusses the city of Vorkuta, which is located in the northwest of Russia. This city differs from many others built on permafrost because most of buildings were built according to Principle II (The Active Method) of construction on permafrost with thawing soil prior to construction. Assessments of the engineering and geocryological conditions, basic principles of construction in the city, and reasons for building failures, were carried out within this study. The research is based on publications, open data about buildings, and visual observations in Vorkuta. About 800 buildings are in use in Vorkuta in 2020 (43% of what it was 50 years ago). According to the analysis, about 800 houses have been demolished or disconnected from utility lines over the past 50 years (about 250 of these are still standing, pending demolition). Since 1994, the construction of new residential buildings has almost stopped. Therefore, buildings that have been in use for over 50 years will account for 90% of the total residential housing stock by 2040. The effects of climate change in the city will depend primarily on the principle of construction employed and on the geocryological conditions of the district. Buildings constructed according to Principle I (The Passive Method) were found to be more vulnerable due to a decrease in permafrost bearing capacity. The impact of increasing air temperature on some of the buildings built on bedrock (the central part of the city) and some built on thawing soil will be minimal, as other factors are more significant.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

ISSN 2071-9388 (Print)
ISSN 2542-1565 (Online)